Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Haas (US 20240260892).
Regarding claims 1 and 10 Haas disclose a mobile device and operating a mobile device to capture anatomical data for a subject and perform an assessment of a functional movement of the subject based on the anatomical data for the subject (Haas, Fig. 1., block 102, paragraph 0039, UE 102 can be any type of device, such as, but not limited to, a mobile phone, tablet, laptop, sensor, wearable device, wearable camera, wearable clothing, a patch, Internet of Things (IoT) device, autonomous machine, and any other type of modern device. In some embodiments, UE 102 can be a device associated with an individual (or set of individuals) for which motion monitoring services are being provided and , Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that track a patient's movement. For example, an accelerometer may measure acceleration, which is the rate of change of the velocity of an object in meters per second squared (m/s.sup.2) or in G-forces (g). Thus, for example, the collected sensor data may indicate a patient's movements), comprising:
processing circuitry and a memory, the memory containing computer readable code that, when executed by the processing circuitry (Hass Figs. 1 and 6-7, paragraph 0243 disclose processing circuitry and a memory, the memory containing computer readable code that, when executed by the processing circuitry),
configures the mobile device to capture anatomical data for a subject and perform an assessment of a functional movement of the subject based on the anatomical data for the subject by (Haas Fig.1 and paragraph 0039 mobile device, paragraph 0082 discloses capturing anatomical data, Figs. 6-7 and paragraph 0243, and paragraphs 0119-0120 Fig. 3B disclose an external device to add data to the system may be used with or without the sensors. The data may be used to inform the system or provide data back to the users. In certain embodiments, a mobile phone may be used to record the video of the wearer, with or without the sensors. The wearer may be instructed to walk, stand still, perform physical exercise, stretch, bend forward, bend backward, twist, squat, lead, bend their head, lay down, or the like. The video may be analyzed to capture information such as gait measurements including but not limited to, stride time, stride length, stride symmetry, two stance phase time, directional deviation, shoulder tilt, pelvic tilt, or metrics such as, but not limited to, range of motion, posture, spinal alignment, or spinal curvature. These metrics may be calculated using any combination of the methods disclosed in this application. These metrics may be tied back to the wearer's data in the system or future data collected by the system, such as the worn devices. Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. This obviously corresponds to configures the mobile device to capture anatomical data for a subject and perform an assessment of a functional movement of the subject based on the anatomical data for the subject by),
capturing the anatomical data for the subject via the mobile device such that the anatomical data includes range of motion (ROM) or postural measurements of one or more joints of the subject determined based on a rotation of the mobile device along a z-axis collected by one or more of an accelerometer and a gyroscope embedded within the mobile device (Haas paragraph 0019-0120 disclose In certain embodiments, a mobile phone may be used to record the video of the wearer, with or without the sensors. The wearer may be instructed to walk, stand still, perform physical exercise, stretch, bend forward, bend backward, twist, squat, lead, bend their head, lay down, or the like. The video may be analyzed to capture information such as gait measurements including but not limited to, stride time, stride length, stride symmetry, two stance phase time, directional deviation, shoulder tilt, pelvic tilt, or metrics such as, but not limited to, range of motion, posture, spinal alignment, or spinal curvature. These metrics may be calculated using any combination of the methods disclosed in this application. Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas paragraph 0035 discloses a user's device that is communicatively connected to the wearable sensor(s) may transmit signals that lead to a change in the user's device and/or wearable device. In some embodiments, this signal may be instructions to start, stop, and/or alter data collection. In some embodiments, this signal may be based on the motion or movement derived from internal sensors such as accelerometers or gyroscopes of the user's device, Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that track a patient's movement. For example, an accelerometer may measure acceleration, which is the rate of change of the velocity of an object in meters per second squared (m/s.sup.2) or in G-forces (g). Thus, for example, the collected sensor data may indicate a patient's movements, breathing, restlessness, twitches, pauses or other detected movements and/or non-movements that may be common during a performance of a task. In some embodiments, sensors 112 also may track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user. Therefore, it is obvious that the system of Haas includes capturing the anatomical data for the subject via the mobile device such that the anatomical data includes range of motion (ROM) or postural measurements of one or more joints of the subject determined based on a rotation of the mobile device along a z-axis collected by one or more of an accelerometer and a gyroscope embedded within the mobile device)
instructing a server to analyze the functional movement of the subject based on the anatomical data and to generate assessment data based on same (Haas paragraph 0035 and 0042 disclose functional motion or movement of user, Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Fig.1-2, paragraph 0051, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device 110 and the UE 102/device 110, sensors 112, imaging device 114, and the services and applications provided by cloud system 106 and/or assessment engine 200, Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106. In some embodiments, assessment engine 200 may function as an application operating via a conventional edge device (not shown) at location associated with system 100, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-18 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring. According to some embodiments, before, during, or after the sensing period, the wearer or another party may wish to view the outputs of the system. In some embodiments, this may come in the form of an application. In some embodiments, such application may provide visuals or graphics in order to inform the wearer or other party. In some embodiments, data may be transmitted to an external device via a wireless communication method or cable in order to provide this display. In some embodiments, data from the device may be transmitted electronically and uploaded to a server enabling remote access to the sensor data. In the system of Haas instructing a server to analyze the functional movement of the subject based on the anatomical data and to generate assessment data based on same), and
displaying, via a user interface of the mobile device, the anatomical data and the assessment of the functional movement of the subject based on the assessment data received from the server (Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas Figs. 1-2, 4A, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-18 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring. According to some embodiments, before, during, or after the sensing period, the wearer or another party may wish to view the outputs of the system. In some embodiments, this may come in the form of an application. In some embodiments, such application may provide visuals or graphics in order to inform the wearer or other party. In some embodiments, data may be transmitted to an external device via a wireless communication method or cable in order to provide this display. This obviously corresponds to displaying, via a user interface of the mobile device, the anatomical data and the assessment of the functional movement of the subject based on the assessment data received from the server).
Therefore, it would be obvious before the filing data of the claimed invention to use mobile device to capture anatomical data for a patient/subject and perform assessment of functional movement of a patient/subject via network/server as shown by Haas because such a system provides automated remote system for monitoring and tracking patient/subject progress overtime during Physiotherapy as stated by Haas in paragraph 0002.
Regarding claim 2 Haas disclose mobile device is further configured to perform an initialization operation to set an initial rotational angle based on an angle the mobile device is positioned on the subject when an initialization command is received from an operator, and to determine the rotation of the mobile device along the z-axis based on the initial rotational angle (Haas Fig. 4 paragraph 0115 disclose In Step 404, engine 200 can effectuate calibration of the placed device (from Step 402). In some embodiments, after the sensors have been affixed to the subject (in Step 402), calibration can take place. In some embodiments, calibration can be based on a set of particular movements or poses. In some embodiments, such poses can include, but are not limited to, bending forward, looking in different directions, twisting, walking, and crouching down, and the like. In some embodiments, the wearer may sway or rotate tracked body parts in particular anatomical planes in order to calibrate the system and paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that tracks a patient's movement. For example, an accelerometer may measure acceleration, which is the rate of change of the velocity of an object in meters per second squared (m/s.sup.2) or in G-forces (g). Thus, for example, the collected sensor data may indicate a patient's movements, breathing, restlessness, twitches, pauses or other detected movements and/or non-movements that may be common during a performance of a task. In some embodiments, sensors 112 also may track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user. Fig 1-2 and paragraphs 0118, 0144 and 0226 UE [mobile device] in communication with network and assessment Engine. Haas Fig. 4, paragraph 0093 disclose engine 200 can utilized a pose estimation algorithm which can be utilized to calibrate the movements and/or poses captured during processing of Step 404 and paragraph 0117 Haas disclose calibration can involve utilizing a camera system, phone, or tablet, whereby the motions can be recorded. In some embodiments, during the calibration period, the worn sensors record measurements while the video is taken. Using the video taken of the subject, these images can be analyzed using AI/ML (e.g., computer vision) to segment the subject and estimate the pose of the subject. In some embodiments, the pose and joints of the subject can be extracted using AI/ML to segment and assess the position of points of interest on the subject and the system. In the system of Haas it would be obvious to mobile device is further configured to perform an initialization operation to set an initial rotational angle based on an angle the mobile device is positioned on the subject when an initialization command is received from an operator, and to determine the rotation of the mobile device along the z-axis based on the initial rotational angle.)
Regarding claim 3 Haas disclose the mobile device is further configured to determine whether the mobile device is positioned horizontally or vertically based on a difference between an acceleration vector which includes components sensed by the accelerometer and an output of the z-axis which is a component sensed by the gyroscope (Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that tracks a patient's movement. For example, an accelerometer may measure acceleration, which is the rate of change of the velocity of an object in meters per second squared (m/s.sup.2) or in G-forces (g). Thus, for example, the collected sensor data may indicate a patient's movements, breathing, restlessness, twitches, pauses or other detected movements and/or non-movements that may be common during a performance of a task. In some embodiments, sensors 112 also may track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user. Fig 1-2 and paragraphs 0118, 0144 and 0226 UE [mobile device] in communication with network and assessment Engine. In the system of Hass it would be obvious to use mobile device to determine whether the mobile device is positioned horizontally or vertically based on a difference between an acceleration vector which includes components sensed by the accelerometer and an output of the z-axis which is a component sensed by the gyroscope because the system of Haas include smart phone including accelerometer or gyroscope that tracks a patient's movement and also track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user).
Regarding claim 4 Haas disclose mobile device is configured to capture the anatomical data for the subject by, calculating a degrees of rotation of the mobile device in a vertical plane based on accelerometer data associated with the accelerometer embedded within the mobile device, in response to the anatomical data being captured while the mobile device is determined as being positioned vertically; and calculating the degrees of rotation in a horizontal plane based on gyroscope data associated with the gyroscope embedded within the mobile device, in response to the anatomical data being captured while the mobile device is determined as being positioned horizontally (Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that tracks a patient's movement. For example, an accelerometer may measure acceleration, which is the rate of change of the velocity of an object in meters per second squared (m/s.sup.2) or in G-forces (g). Thus, for example, the collected sensor data may indicate a patient's movements, breathing, restlessness, twitches, pauses or other detected movements and/or non-movements that may be common during a performance of a task. In some embodiments, sensors 112 also may track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user. Fig 1-2 and paragraphs 0118, 0144 and 0226 UE [mobile device] in communication with network and assessment Engine. In the system of Haas it would be obvious to capture the anatomical data for the subject by, calculating a degrees of rotation of the mobile device in a vertical plane based on accelerometer data associated with the accelerometer embedded within the mobile device, in response to the anatomical data being captured while the mobile device is determined as being positioned vertically; and calculating the degrees of rotation in a horizontal plane based on gyroscope data associated with the gyroscope embedded within the mobile device, in response to the anatomical data being captured while the mobile device is determined as being positioned horizontally because the system of Haas include smart phone including accelerometer or gyroscope that tracks a patient's movement and also track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user).
Regarding claim 5 Haas disclose the mobile device is configured to display the assessment of the functional movement by displaying one or more of functional movement scores, a joint mobility score, severity categories, an overall mobility score, and an avatar of the subject (Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas Figs. 1-2, 4A, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-18 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring. According to some embodiments, before, during, or after the sensing period, the wearer or another party may wish to view the outputs of the system. In some embodiments, this may come in the form of an application. In some embodiments, such application may provide visuals or graphics in order to inform the wearer or other party. In some embodiments, data may be transmitted to an external device via a wireless communication method or cable in order to provide this display. Further Haas paragraph 0183 discloses Step 408, engine 200 can effectuate the performance of user instruction. According to some embodiments, the wearer can be instructed to perform a number of tasks when wearing the system. In some embodiments, such tasks can include certain stretches to test range of motion, certain compound movements to test patient balance and mobility, and/or a walking test to track gait parameters and posture. In some embodiments, the tests can be used to create a score for the use in clinical settings or as an informative metric for the wearer. In some embodiments, when performing these tasks, a video may be simultaneously taken to record these events. In some embodiments, there may be instructions given through a tablet or other digital devices to display instructions for the tasks and paragraph 0199 Haas disclose the computational analysis may factor in, but is not limited to, motion, posture, activity, compensation, and pain prediction and processing through AI/ML (e.g., deep learning) techniques. In some embodiments, the data analyzed may include summarized positioning and activity data displayed in table, numeric, or figure format. In some embodiments, the disclosed analysis may create a score for usage by the user to interpret the overall status of the wearer. In some embodiments, this score may be compared to previous readings, a generalized standard, or may be interpreted for other uses. Therefore, it is obvious that the system of Haas includes the mobile device is configured to display the assessment of the functional movement by displaying one or more functional movement scores, a joint mobility score, severity categories, an overall mobility score, and an avatar of the subject).
Regarding claim 6 Haas disclose mobile device is further configured to collect metadata associated with the anatomical data and transmit the metadata to the server, the metadata including at least time data, subject data and operator data (Figs. 1-2, Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that tracks a patient's movement, Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106, Haas paragraph 0066 In some embodiments, “activity level” can correspond to, but not be limited to, values, metrics and/or other forms of data/metadata indicating steps, standing time, walking time, distance, fatigue throughout the day, and the like, or some combination thereof and Haas paragraph 0051, In some embodiments, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device. All this obviously corresponds to mobile device is further configured to collect metadata associated with the anatomical data and transmit the metadata to the server, the metadata including at least time data, subject data and operator data), and
the server is configured to analyze the functional movement based on the anatomical data and the metadata (Haas paragraphs 0051, 0066 disclose metadata, and paragraphs 0035 and 0042 disclose functional motion or movement of user, Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider, Fig.1-2, paragraph 0051, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device 110 and the UE 102/device 110, sensors 112, imaging device 114, and the services and applications provided by cloud system 106 and/or assessment engine 200. This obviously corresponds to the server is configured to analyze the functional movement based on the anatomical data and the metadata) by,
obtaining demographic-specific insights applicable to the subject based on the subject data (Haas Fig. 4, paragraphs 0108 and 0217 disclose In some embodiments, Step 402 can involve activation and assignment of an identifier (ID) for the device/sensor and/or patient. In some embodiments, this information can be stored in database 108, which can be stored along with biographic and demographic information about the patient, inter alia other forms of data related to the patient and procedure and in some embodiments, the digital interface may allow providers to track statistics and metrics of their choosing. These may be statistics of patient demographic intervention types and frequencies, cases done, patients seen, time with patients, time planning interventions, number of devices utilized, or other metrics relevant to the system and the data collected and Haas claims 4 and 13. This obviously corresponds to obtaining demographic-specific insights applicable to the subject based on the subject data),
analyzing the functional movement of the subject across different time periods, which are identified based on the time data (Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider, Haas paragraph 0184 In some embodiments, a walking test is performed by the wearer. In some embodiments these may occur multiple times throughout the course of wearing the sensors and comparisons of the data may be used in the analysis. In some embodiments, during the course of the walking test, the posture of the spine is monitored. In some embodiments, segments of the spine may be monitored in order to determine changes in angle or motion. In some embodiments, gait metric may also be collected to provide insights into the health and mobility of the patient and Haas paragraph 0217 in some embodiments, the digital interface may allow providers to track statistics and metrics of their choosing. These may be statistics of patient demographic intervention types and frequencies, cases done, patients seen, time with patients, time planning interventions. This obviously corresponds to analyzing the functional movement of the subject across different time periods, which are identified based on the time data and claim 5 of Haas recites analyzing the user information via an executed large language model (LLM); and determining additional information related to at least one of a medical diagnosis, initial symptoms and initial observations related to the user, wherein the additional information is further utilized to determine the metrics of the user) and
linking the anatomical data to a specific operator of the mobile device based on the operator data such that the server is configured to generate quality control data indicating an accuracy of the assessment conducted by different operators (Haas Figs. 1-2, 4 paragraphs 0108 and 0217 disclose In some embodiments, Step 402 can involve activation and assignment of an identifier (ID) for the device/sensor and/or patient. In some embodiments, this information can be stored in database 108, which can be stored along with biographic and demographic information about the patient, inter alia other forms of data related to the patient and procedure and in some embodiments, the digital interface may allow providers to track statistics and metrics of their choosing. These may be statistics of patient demographic intervention types and frequencies, cases done, patients seen, time with patients, time planning interventions, number of devices utilized, or other metrics relevant to the system. In the system of Haas it is obvious that the demographic (operator/user) data and anatomical data i.e. anatomical movement/motion data are logged or stored in database as stated above in paragraph 0217 and shown in Figs. 1-2 therefore it is obvious that demographic/user data and anatomical motion/movement statistic and metrics are linked in the database specific to operator/user/patient and Haas claim 5, recites analyzing the user information via an executed large language model (LLM) and determining additional information related to at least one of a medical diagnosis, initial symptoms and initial observations related to the user, wherein the additional information is further utilized to determine the metrics of the user. Therefore the system of Haas obviously include linking the anatomical data to a specific operator of the mobile device based on the operator data such that the server is configured to generate quality control data indicating an accuracy of the assessment conducted by different operators by correlating/linking motion/movement metric and demographic of user to determine the quality of collected and analyze motion/movement metric data overtime).
Regarding claim 7 Haas disclose mobile device is further configured to instruct an operator thereof to capture the anatomical data associated with different ones of the ROM or postural measurements (Haas paragraph 0183 discloses Step 408, engine 200 can effectuate the performance of user instruction. According to some embodiments, the wearer can be instructed to perform a number of tasks when wearing the system. In some embodiments, such tasks can include certain stretches to test range of motion, certain compound movements to test patient balance and mobility, and/or a walking test to track gait parameters and posture. In some embodiments, the tests can be used to create a score for the use in clinical settings or as an informative metric for the wearer. In some embodiments, when performing these tasks, a video may be simultaneously taken to record these events. In some embodiments, there may be instructions given through a tablet or other digital devices to display instructions for the tasks and paragraph 0199 Haas disclose the computational analysis may factor in, but is not limited to, motion, posture, activity, compensation, and pain prediction and processing through AI/ML (e.g., deep learning) techniques. In some embodiments, analyzed data may include summarized positioning and activity data displayed in table, numeric, or figure format)
Regarding claim 8 Haas disclose mobile device is configured to instruct the operator thereof to capture the anatomical data associated with each of the ROM or postural measurements in a set order, the set order being customizable and reusable by the operator when evaluating different ones of a plurality of subjects (Haas Figs. 1-2 3C-3D, and 4A, paragraph 0075, paragraph 0183 discloses Step 408, engine 200 can effectuate the performance of user instruction. According to some embodiments, the wearer can be instructed to perform a number of tasks when wearing the system. In some embodiments, such tasks can include certain stretches to test range of motion, certain compound movements to test patient balance and mobility, and/or a walking test to track gait parameters and posture. In some embodiments, the tests can be used to create a score for the use in clinical settings or as an informative metric for the wearer. In some embodiments, when performing these tasks, a video may be simultaneously taken to record these events. In some embodiments, there may be instructions given through a tablet or other digital devices and Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas Figs. 1-2, 4A, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-18 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring. Therefore, in the system of Haas it would be obvious that mobile device is configured to instruct the operator thereof to capture the anatomical data associated with each of the ROM or postural measurements in a set order, the set order being customizable and reusable by the operator when evaluating different ones of a plurality of subjects).
Regarding claim 9 Haas disclose mobile device is configured to allow the operator to skip or redo the capturing of the anatomical data associated with one or more the ROM or postural measurements in response to input from the operator (Haas paragraph 0035 and 0042 disclose functional motion or movement of user, Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that track a patient's movement and paragraph 0075 In some embodiments, as provided below, process 400 can involve Steps 402-418, which as provided below, respectively involve placement, calibration, sensing, user instruction, live monitoring, remove, upload, analysis and data review. In some embodiments, the steps provided in Process 400 related to user instruction (Step 408), live monitoring (Step 410), remove (Step 412) and upload (Step 414) may be optional, and/or performed in a different order as depicted in FIG. 4A. As shown in Figs 1-2 Haas system is digital and it would be obvious to program the system of Haas to remove/skip and redo some movement/motion based on the data review ).
Regarding claims 11 and 19 Haas disclose a server and operating a server to analyze functional movement of a subject based on anatomical data for the subject, (Haas Figs. 1-2, Haas paragraph 0035 and 0042 disclose functional motion or movement of user, Fig.1-2, paragraph 0051, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device 110 and the UE 102/device 110, sensors 112, imaging device 114, and the services and applications provided by cloud system 106 and/or assessment engine 200, Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106), comprising:
processing circuitry and a memory, the memory containing computer readable code that, when executed by the processing circuitry, configures the server to analyze functional movement of a subject based on anatomical data for the subject by (Hass Figs. 1 and 6-7, paragraph 0243 disclose processing circuitry and a memory, the memory containing computer readable code that, when executed by the processing circuitry, Hass Figs. 1 and 6-7, paragraph 0243 disclose processing circuitry and a memory, the memory containing computer readable code that, when executed by the processing circuitry. Haas Fig.1 and paragraph 0039 mobile device, paragraph 0082 discloses capturing anatomical data, Figs. 6-7 and paragraph 0243, and paragraphs 0119-0120 Fig. 3B disclose an external device to add data to the system may be used with or without the sensors. The data may be used to inform the system or provide data back to the users. In certain embodiments, a mobile phone may be used to record the video of the wearer, with or without the sensors. The wearer may be instructed to walk, stand still, perform physical exercise, stretch, bend forward, bend backward, twist, squat, lead, bend their head, lay down, or the like. The video may be analyzed to capture information such as gait measurements including but not limited to, stride time, stride length, stride symmetry, two stance phase time, directional deviation, shoulder tilt, pelvic tilt, or metrics such as, but not limited to, range of motion, posture, spinal alignment, or spinal curvature. Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106. In some embodiments, assessment engine 200 may function as an application operating via a conventional edge device (not shown) at location associated with system 100, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-418 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring,
This obviously corresponds to processing circuitry and a memory, the memory containing computer readable code that, when executed by the processing circuitry, configures the server to analyze functional movement of a subject based on anatomical data for the subject),
receiving the anatomical data for the subject captured by a mobile device, the anatomical data including range of motion (ROM) or postural measurements of one or more joints of the subject determined based on a rotation of the mobile device along a z-axis collected by one or more of an accelerometers and a gyroscope embedded within the mobile device ((Haas paragraph 0019-0120 disclose In certain embodiments, a mobile phone may be used to record the video of the wearer, with or without the sensors. The wearer may be instructed to walk, stand still, perform physical exercise, stretch, bend forward, bend backward, twist, squat, lead, bend their head, lay down, or the like. The video may be analyzed to capture information such as gait measurements including but not limited to, stride time, stride length, stride symmetry, two stance phase time, directional deviation, shoulder tilt, pelvic tilt, or metrics such as, but not limited to, range of motion, posture, spinal alignment, or spinal curvature. These metrics may be calculated using any combination of the methods disclosed in this application. Haas paragraph 0035 discloses a user's device that is communicatively connected to the wearable sensor(s) may transmit signals that lead to a change in the user's device and/or wearable device. In some embodiments, this signal may be instructions to start, stop, and/or alter data collection. In some embodiments, this signal may be based on the motion or movement derived from internal sensors such as accelerometers or gyroscopes of the user's device, Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that track a patient's movement. For example, an accelerometer may measure acceleration, which is the rate of change of the velocity of an object in meters per second squared (m/s.sup.2) or in G-forces (g). Thus, for example, the collected sensor data may indicate a patient's movements, breathing, restlessness, twitches, pauses or other detected movements and/or non-movements that may be common during a performance of a task. In some embodiments, sensors 112 also may track and/or collect x, y, z coordinates of the user and/or UE 102 in order to detect the movements of the user. Fig 1-2 and paragraphs 0118, 0144 and 0226 UE [mobile device] in communication with network and assessment Engine. This obviously corresponds to receiving the anatomical data for the subject captured by a mobile device, the anatomical data including range of motion (ROM) or postural measurements of one or more joints of the subject determined based on a rotation of the mobile device along a z-axis collected by one or more of an accelerometer and a gyroscope embedded within the mobile device,
storing the anatomical data in a database within a memory device (Haas paragraph 0035 and 0042 disclose functional motion or movement of user, Fig.1-2, paragraph 0051, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device 110 and the UE 102/device 110, sensors 112, imaging device 114, and the services and applications provided by cloud system 106 and/or assessment engine 200 and Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. . This obviously corresponds to storing the anatomical data in a database within a memory device),
analyzing the functional movement of the one or more joints of the subject based on the ROM or postural measurements and database information (Haas paragraph 0035 and 0042 disclose functional motion or movement of user, Fig.1-2, paragraph 0051, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device 110 and the UE 102/device 110, sensors 112, imaging device 114, and the services and applications provided by cloud system 106 and/or assessment engine 200, Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106. In some embodiments, assessment engine 200 may function as an application operating via a conventional edge device (not shown) at location associated with system 100, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-18 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring. According to some embodiments, before, during, or after the sensing period, the wearer or another party may wish to view the outputs of the system. In some embodiments, this may come in the form of an application. In some embodiments, such application may provide visuals or graphics in order to inform the wearer or other party. In some embodiments, data may be transmitted to an external device via a wireless communication method or cable in order to provide this display. In some embodiments, data from the device may be transmitted electronically and uploaded to a server enabling remote access to the sensor data), and
transmitting results of the analyzing of the functional movement of the one or more joints of the subject to the mobile device (Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106. In some embodiments, assessment engine 200 may function as an application operating via a conventional edge device (not shown) at location associated with system 100, Haas paragraph 0058 as illustrated in FIG. 2, according to some embodiments, assessment engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208, Haas Fig. 4A, blocks 414-18 and paragraph 0186 discloses In Step 410, engine 200 can perform instructions related to live monitoring. According to some embodiments, before, during, or after the sensing period, the wearer or another party may wish to view the outputs of the system. In some embodiments, this may come in the form of an application. In some embodiments, such application may provide visuals or graphics in order to inform the wearer or other party. In some embodiments, data may be transmitted to an external device via a wireless communication method or cable in order to provide this display. In the system of Haas this obviously corresponds to transmitting results of the analyzing of the functional movement of the one or more joints of the subject to the mobile device. This obviously corresponds to transmitting results of the analyzing of the functional movement of the one or more joints of the subject to the mobile device).
Therefore, it would be obvious before the filing data of the claimed invention to use mobile device to capture anatomical data for a patient/subject and perform assessment of functional movement of a patient/subject via network/server as shown by Haas because such a system provides automated remote system for monitoring and tracking patient/subject progress overtime during Physiotherapy as stated by Haas in paragraph 0002.
Regarding claim 12 Haas disclose the server is configured to, receive metadata associated with the anatomical data for the subject from the mobile device such that the metadata includes at least time data, subject data, and operator data (Figs. 1-2, Haas paragraph 0042 disclose UE 102 can have associated therewith a plurality of sensors 112 to collect data from a user. By way of a non-limiting example, the sensors 112 can include the sensors on UE 102 (e.g., smart phone) and/or peripheral device 110 (e.g., a paired smart watch). For example, sensors 112 may be, but are not limited to, an accelerometer or gyroscope that tracks a patient's movement, Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider. Haas paragraph 0057 assessment engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a server(s), network location and/or other type of network resource associated with system 106, Haas paragraph 0066 In some embodiments, “activity level” can correspond to, but not be limited to, values, metrics and/or other forms of data/metadata indicating steps, standing time, walking time, distance, fatigue throughout the day, and the like, or some combination thereof and Haas paragraph 0051, In some embodiments, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device. This obviously corresponds to the server is configured to, receive metadata associated with the anatomical data for the subject from the mobile device such that the metadata includes at least time data, subject data, and operator data), and
analyze the functional movement based on the anatomical data and the metadata (Haas paragraphs 0051, 0066 disclose metadata, and paragraphs 0035 and 0042 disclose functional motion or movement of user, Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider, Fig.1-2, paragraph 0051, cloud system 106 may include a server(s) and/or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and/or network information related to a user(s) of UE 102/device 110 and the UE 102/device 110, sensors 112, imaging device 114, and the services and applications provided by cloud system 106 and/or assessment engine 200. This obviously corresponds to analyze the functional movement based on the anatomical data and the metadata. This obviously corresponds to analyzing the functional movement of the subject across different time periods, which are identified based on the time data and meta data) by
obtaining demographic-specific insights applicable to the subject based on the subject data (Haas Fig. 4, paragraphs 0108 and 0217 disclose In some embodiments, Step 402 can involve activation and assignment of an identifier (ID) for the device/sensor and/or patient. In some embodiments, this information can be stored in database 108, which can be stored along with biographic and demographic information about the patient, inter alia other forms of data related to the patient and procedure and in some embodiments, the digital interface may allow providers to track statistics and metrics of their choosing. These may be statistics of patient demographic intervention types and frequencies, cases done, patients seen, time with patients, time planning interventions, number of devices utilized, or other metrics relevant to the system and the data collected and Haas claims 4 and 13. This obviously corresponds to obtaining demographic-specific insights applicable to the subject based on the subject data),
analyzing the functional movement of the subject across different time periods, which are identified based on the time data ((Haas paragraph 0120 models may be used to calculate the location of scene objects, such as the floor and used to transform the collected data or to detect events such as steps. The data may be processed, and reports generated such as joint range of motion, joint stability, walking speed, varus or valgus knee angle measurements, or any other measure of interest dictated by the care provider. This data may be logged in a database to be viewed by both the patient and the provider, Haas paragraph 0184 In some embodiments, a walking test is performed by the wearer. In some embodiments these may occur multiple times throughout the course of wearing the sensors and comparisons of the data may be used in the analysis. In some embodiments, during the course of the walking test, the posture of the spine is monitored. In some embodiments, segments of the spine may be monitored in order to determine changes in angle or motion. In some embodiments, gait metric may also be collected to provide insights into the health and mobility of the patient and Haas paragraph 0217 in some embodiments, the digital interface may allow providers to track statistics and metrics of their choosing. These may be statistics of patient demographic intervention types and frequencies, cases done, patients seen, time with patients, time planning interventions. This obviously corresponds to analyzing the functional movement of the subject across different time periods, which are identified based on the time data and claim 5 of Haas recites analyzing the user information via an executed large language model (LLM); and determining additional information related to at least one of a medical diagnosis, initial symptoms and initial observations related to the user, wherein the additional information is further utilized to determine the metrics of the user. This obviously corresponds to analyzing the functional movement of the subject across different time periods, which are identified based on the time data),
linking the anatomical data to a specific operator of the mobile device based on the operator data such that the server is configured to generate quality control data indicating an accuracy of the assessment conducted by different operators ((Haas Figs. 1-2, 4 paragraphs 0108 and 0217 disclose In some embodiments, Step 402 can involve activation and assignment of an identifier (ID) for the device/sensor and/or patient. In some embodiments, this information can be stored in database 108, which can be stored along with biographic and demographic information about the patient, inter alia other forms of data related to the patient and procedure and in some embodiments, the digital interface may allow providers to track statistics and metrics of their choosing. These may be statistics of patient demographic intervention types and frequencies, cases done, patients seen, time with patients, time planning interventions, number of devices utilized, or other metrics relevant to the system. In the system of Haas it is obvious that the demographic (operator/user) data and anatomical data i.e. anatomical movement/motion data are logged or stored in database as stated above in paragraph 0217 and shown in Figs. 1-2 therefore it is obvious that demographic/user data and anatomical motion/movement statistic and metrics are linked in the database specific to operator/user/patient and Haas claim 5, recites analyzing the user information via an executed large language model (LLM) and determining additional information related to at least one of a medical diagnosis, initial symptoms and initial observations related to the user, wherein the additional information is further utilized to determine the metrics of the user. Therefore the system of Haas obviously include linking the anatomical data to a specific operator of the mobile device based on the operator data such that the server is configured to generate quality control data indicating an accuracy of the assessment conducted by different operators by correlating/linking motion/movement metric and demographic of user to determine the quality of collected and analyze motion/movement metric data overtime).
Allowable Subject Matter Claims 13-18 and 20 are objected as being dependent on rejected base claim but would be allowable over the prior art of record if rewritten in the independent form including limitations of the base claim and any intervening claims.
Communication Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISHRAT I SHERALI whose telephone number is (571)272-7398. The examiner can normally be reached Monday-Friday 8:00AM -5:00 PM.
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ISHRAT I. SHERALI
Examiner
Art Unit 2667
/ISHRAT I SHERALI/Primary Examiner, Art Unit 2667
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