DETAILED ACTION
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 Status: Claims 1-30 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-6 and 21-24 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Re Claim 2, the limitation “a breathing event” is indefinite, because it is unclear whether it is referring to “a breathing event” in claim 1 or a different one.
Re Claim 3, the limitation “the breathing event data” is indefinite, because it is unclear whether it is referring to “the data to identify a breathing event” or “stored breathing event data” in claim 2.
Re Claim 21, the limitation “the breathing event data” is indefinite, because it is unclear whether it is referring to “the breathing event” or “stored breathing event data” in claim 20.
Indefiniteness of claims 2, 3, and 21 renders their dependent claims 4-6 and 22-24 indefinite.
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 (i.e., changing from AIA to pre-AIA ) 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 1-3, 7-21, and 25-30 are rejected under 35 U.S.C. 103 as being unpatentable over Kacyvenski (US 2015/0019135) in view of Murgas (US 2021/0113114), Bennett-Guerrero (US 2015/0257654A1), and Patel (US 2016/0249174A1).
Re Claims 1-3, 7-9, and 15, Kacyvenski discloses a method for operating a computing system including one or more processors to identify breathing events of a subject, comprising:
receiving, by the one or more processors, data from a plurality of sensors, including a plurality of motion sensors (para. [0205], conformal sensor devices, para. [0212], The example conformal sensor devices herein include one or more sensor components, such as but not limited to triaxial accelerometers and/or gyroscopes, that can be implemented to measure the body mechanics during the throwing action and over a series of throwing sessions; para. [0259], EMG and accelerometer to measure respiratory rhythms and movement), mounted to an article positioned on an upper body of the subject (para. [0205], form-fitting apparel including, but not limited to shirts or sporting apparel),
wherein the data includes data associated with movement of an upper body of the subject (para. [0212], triaxial accelerometers and/or gyroscopes, can be implemented to measure the body mechanics during the throwing action and over a series of throwing sessions. The example conformal sensor devices facilitate flexible placement methods, and therefore so can be placed on any portion of the body, including the hand, wrist, forearm, upper arm, shoulder, or any other applicable body part; para. [0259], fig. 25, Example conformal sensor system 2502 can be disposed on or otherwise coupled to the thoracic diaphragm, to measure respiratory rhythms and movement.);
processing the data, by the one or more processors, to identify a breathing event of the subject (para. [0259], fig. 25, Example conformal sensor system 2502 can be disposed on or otherwise coupled to the thoracic diaphragm, to measure respiratory rhythms and movement; Table 1, Muscle activity may indicate relaxation level and indicate bruxism).
Kacyvenski is silent regarding wherein the identified breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a cough event, a sneeze event, a choke event, a scream event, and an apnea event, wherein processing the data comprises processing the data by a trained model, wherein processing the data comprises processing the data by a trained artificial neural network, and training the model, wherein processing the data to identify a breathing event comprises comparing the data to stored breathing event data and receiving and storing the breathing event data.
However, Murgas discloses at least one motion sensor placed on a chest wall to produce at least one sensor output signal dependent upon respiratory motion of the chest wall of the subject (abstract) and processing the data, by one or more processors, to identify a breathing event of the subject, wherein the identified breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a cough event, a sneeze event, a choke event, a scream event, and an apnea event, wherein processing the data comprises processing the data by a trained model, wherein processing the data comprises processing the data by a trained artificial neural network, wherein processing the data to identify a breathing event comprises comparing the data to stored breathing event data (para. [0085], The trained machine learning system 20 can classify breathing patterns and identify breathing patterns that deviate from a reference breathing pattern(s) using the respiration measurement output 21. It can, for example, detect a breathing pattern produced by sleep apnea; para. [0080], trained neural network), and training the model (para. [0080], FIG. 6A illustrates the training process that calibrate the system. During the calibration process various sensor output signals 11 are provided to the machine learning algorithm along with corresponding absolute values of respiration volume as training data; para. [0124], The data may, for example, be used as learning input to train a machine learning network.). Murgas discloses receiving and storing the breathing event data (para. [0110], [0117]-[0119], data may be stored; para. [0124], The processing of the data, whether local or remote, may involve artificial intelligence or machine learning algorithms. The data may, for example, be used as learning input to train a machine learning network or may be used as a query input to a machine learning network, which provides a response.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski, by processing the data, by one or more processors, to identify a breathing event of the subject, wherein the identified breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a cough event, a sneeze event, a choke event, a scream event, and an apnea event, wherein processing the data comprises processing the data by a trained model, wherein processing the data comprises processing the data by a trained artificial neural network, wherein processing the data to identify a breathing event comprises comparing the data to stored breathing event data, training the model, and receiving and storing the breathing event data, as taught by Murgas, for the purpose of detecting sleep apnea by the breathing patterns (para. [0085]) and further refining the algorithm that detects sleep apnea (para. [0124]).
Kacyvenski discloses a motion sensor mounted to the article at position corresponding to abdomen (para. [0089], at least one conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen; para. [0205], form-fitting apparel including, but not limited to shirts or sporting apparel; para. [0121]).
Kacyvenski and Murgas are silent regarding wherein at least two of the plurality of motion sensors are mounted to the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a first of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and above an umbilicus of the subject, and at least a second of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and below the umbilicus of the subject, wherein processing the data to identify a breathing event includes determining an angle of the upper body of the subject based upon data from sensors including the at least two of the plurality of motion sensors mounted at positions corresponding to the midline of the anterior portion of the subject, the at least first of the plurality of motion sensors mounted at the position proximate to and above the umbilicus, and the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus. ;
Bennett-Guerrero discloses a motion sensor mounted to an article (para. [0482], The sensor and/or attachment mechanism can include a material or other apparatus that is attachable to a patient's body, either directly or indirectly. Indirectly attached, such as by being attached to the patient's cloths, such as the patient's hospital gown or other article of clothing) at position corresponding to an anterior portion of the subject and proximate to and above an umbilicus of a subject and determining an angle of the upper body of the subject based on data from the motion sensor (para. [0199], an accelerometer is used to measure the angle of incline of the patient’s upper abdomen; para. [0480], attached incline sensor accurately measures the incline of a relevant body area (e.g., upper abdomen/chest); para. [0200], supine or prone position) for the purpose of reducing or preventing reflux and/or aspiration (para. [0216]), facilitating or ensuring adequate head of bed elevations for certain patients, such as those receiving mechanical ventilation, patients being enterally fed (para. [0199]) and monitoring sleep position and detecting sleep apnea (para. [0200]; para. [0098]).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, by adding a motion sensor mounted to the article at position corresponding to an anterior portion of the subject, wherein at least a first of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and above an umbilicus of the subject, wherein processing the data to identify a breathing event includes determining an angle of the upper body of the subject based upon data from the motion sensor mounted at positions corresponding to the anterior portion of the subject, the at least first of the plurality of motion sensors mounted at the position proximate to and above the umbilicus, as taught by Bennett-Guerrero, for the purpose of reducing or preventing reflux and/or aspiration (para. [0216]), facilitating or ensuring adequate head of bed elevations for certain patients, such as those receiving mechanical ventilation, patients being enterally fed (para. [0199]), monitoring sleep position and detecting sleep apnea (para. [0200]; para. [0098]).
Bennett-Guerrero is silent regarding wherein a second sensor mounted to the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and below the umbilicus of the subject, wherein processing the data to identify a breathing event includes determining an angle of the upper body of the subject based upon data from second sensor mounted at position corresponding to the midline of the anterior portion of the subject, the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus.
However, Patel discloses a second sensor mounted to the article (para. [0011], The wearable electronic device can be adhered to the body by an adhesive or positioned against the body by straps or clothing) at position corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and below the umbilicus of the subject (fig. 3, ref# 303e) and determining an angle of the upper body of the subject based upon data from second sensor mounted at position corresponding to the midline of the anterior portion of the subject, the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus (fig. 3, ref# 303e, para. [0074], Wearable device 303 e is located on the lower abdomen of the user 301 and may be for monitoring blood flow and/or posture of the user; para. [0171], [0190], accelerometer is used for measuring posture).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas and Bennett-Guerrero, by adding a second sensor mounted to the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and below the umbilicus of the subject, wherein processing the data to identify a breathing event includes determining an angle of the upper body of the subject based upon data from the second sensor mounted at position corresponding to the midline of the anterior portion of the subject, the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus, as taught by Patel, for the purpose of measuring posture (para. [0074]).
Bennett-Guerrero is silent regarding the first motion sensor positioned corresponding to the midline of the anterior portion of the subject.
However, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, Bennett-Guerrero, and Patel, by positioning the at least first motion sensor corresponding to the midline of the anterior portion of the subject, because such a modification would have been obvious to try since there are finite potential locations to place the motion sensor to measure upper body posture with a reasonable level of success and one of ordinary skill in the art could have pursued the known potential location with a reasonable expectation of success.
Re Claims 16, 19, 20, 21, and 25, Kacyvenski discloses a system for identifying breathing events of a subject, comprising:
an article configured to be positioned on an upper body of the subject (para. [0205], form-fitting apparel including, but not limited to shirts or sporting apparel),
the article including a plurality of sensors, including a plurality of motion sensors, for sensing subject data (para. [0205], conformal sensor devices, para. [0212], The example conformal sensor devices herein include one or more sensor components, such as but not limited to triaxial accelerometers and/or gyroscopes, that can be implemented to measure the body mechanics during the throwing action and over a series of throwing sessions; para. [0259], EMG and accelerometer to measure respiratory rhythms and movement); and
a computer system including one or more processors (para. [0265], programmable processor and a computer),
wherein the computer system is configured to receive the subject data and to identify a breathing event of the subject (para. [0259], EMG and accelerometer to measure respiratory rhythms and movement; Table I, respiratory rate sensing),
Kacyvenski is silent regarding wherein the breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a cough event, a sneeze event, a choke event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a scream event, and an apnea event, wherein the computer system identifies the breathing event at least in part by comparing the subject data to stored breathing event data, wherein the computer system identifies the breathing event at least in part by processing the subject data by a trained model, wherein the computer system receives and stores the breathing event data.
However, Murgas discloses at least one motion sensor placed on a chest wall to produce at least one sensor output signal dependent upon respiratory motion of the chest wall of the subject (abstract).
Murgas discloses a computer system configured to receive subject data and to identify a breathing event of the subject, wherein the breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a cough event, a sneeze event, a choke event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a scream event, and an apnea event, wherein the computer system identifies the breathing event at least in part by comparing the subject data to stored breathing event data, wherein the computer system identifies the breathing event at least in part by processing the subject data by a trained model (para. [0085], The trained machine learning system 20 can classify breathing patterns and identify breathing patterns that deviate from a reference breathing pattern(s) using the respiration measurement output 21. It can, for example, detect a breathing pattern produced by sleep apnea; para. [0080], trained neural network). Murgas discloses that the computer system receives and stores the breathing event data (para. [0110], [0117]-[0119], data may be stored; para. [0124], The processing of the data, whether local or remote, may involve artificial intelligence or machine learning algorithms. The data may, for example, be used as learning input to train a machine learning network or may be used as a query input to a machine learning network, which provides a response.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski, by configuring the computer system to receive subject data and to identify a breathing event of the subject, wherein the breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a cough event, a sneeze event, a choke event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a scream event, and an apnea event, wherein the computer system identifies the breathing event at least in part by comparing the subject data to stored breathing event data, wherein the computer system identifies the breathing event at least in part by processing the subject data by a trained model, wherein the computer system receives and stores the breathing event data, as taught by Murgas, for the purpose of detecting sleep apnea by the breathing patterns (para. [0085]) and further refining the algorithm that detects sleep apnea (para. [0124]).
Kacyvenski discloses a motion sensor mounted to the article at position corresponding to abdomen (para. [0089], at least one conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen; para. [0205], form-fitting apparel including, but not limited to shirts or sporting apparel; para. [0121]).
Kacyvenski and Murgas are silent regarding wherein at least two of the plurality of motion sensors are located on the article at positions corresponding to a midline of an anterior portion of the subject; wherein at least a first of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and above an umbilicus of the subject, and at least a second of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and below the umbilicus of the subject; wherein the computer system identifies the breathing event at least in part by determining an angle of the upper body of the subject based upon subject data from sensors including the at least two of the plurality of motion sensors mounted at positions corresponding to the midline of the anterior portion of the subject, the at least first of the plurality of motion sensors mounted at the position proximate to and above the umbilicus, and the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus.
Bennett-Guerrero discloses a motion sensor located on an article (para. [0482], The sensor and/or attachment mechanism can include a material or other apparatus that is attachable to a patient's body, either directly or indirectly. Indirectly attached, such as by being attached to the patient's cloths, such as the patient's hospital gown or other article of clothing) at position corresponding to an anterior portion of the subject and proximate to and above an umbilicus of a subject, wherein a computer system identifies the breathing event at least in part by determining an angle of the upper body of the subject based on data from the motion sensor (para. [0199], an accelerometer is used to measure the angle of incline of the patient’s upper abdomen; para. [0480], attached incline sensor accurately measures the incline of a relevant body area (e.g., upper abdomen/chest); para. [0200], supine or prone position) for the purpose of reducing or preventing reflux and/or aspiration (para. [0216]), facilitating or ensuring adequate head of bed elevations for certain patients, such as those receiving mechanical ventilation, patients being enterally fed (para. [0199]) and monitoring sleep position and detecting sleep apnea (para. [0200]; para. [0098], 1) to diagnose sleep-related conditions, including but limited to sleep apnea, 2) determining whether a patient is asleep or awake for the purpose of setting parameters relating to respiration, heart rate, etc. However, other embodiments include sensor(s) and/or sensor system(s) that can be applied in the context of monitoring other aspects of, or conditions directly or indirectly related to, sleep, including but not limited to duration, position, movements, quality, etc.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, by adding a motion sensor located on the article at position corresponding to an anterior portion of the subject, wherein at least a first of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and above an umbilicus of the subject, wherein the computer system identifies the breathing event at least in part by determining an angle of the upper body of the subject based upon data from the motion sensor mounted at positions corresponding to the anterior portion of the subject, the at least first of the plurality of motion sensors mounted at the position proximate to and above the umbilicus, as taught by Bennett-Guerrero, for the purpose of reducing or preventing reflux and/or aspiration (para. [0216]), facilitating or ensuring adequate head of bed elevations for certain patients, such as those receiving mechanical ventilation, patients being enterally fed (para. [0199]), monitoring sleep position and detecting sleep apnea (para. [0200]; para. [0098]).
Bennett-Guerrero is silent regarding wherein a second sensor located on the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and below the umbilicus of the subject, wherein the computer system identifies the breathing event at least in part by determining an angle of the upper body of the subject based upon subject data from second sensor mounted at position corresponding to the midline of the anterior portion of the subject, the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus.
However, Patel discloses a second sensor located on the article (para. [0011], The wearable electronic device can be adhered to the body by an adhesive or positioned against the body by straps or clothing) at position corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and below the umbilicus of the subject (fig. 3, ref# 303e) and determining an angle of the upper body of the subject based upon data from second sensor mounted at position corresponding to the midline of the anterior portion of the subject, the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus (fig. 3, ref# 303e, para. [0074], Wearable device 303 e is located on the lower abdomen of the user 301 and may be for monitoring blood flow and/or posture of the user; para. [0171], [0190], accelerometer is used for measuring posture).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas and Bennett-Guerrero, by adding a second sensor located on the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and below the umbilicus of the subject, wherein the computer system identifies the breathing event at least in part by determining an angle of the upper body of the subject based upon data from the second sensor mounted at position corresponding to the midline of the anterior portion of the subject, the at least second of the plurality of motion sensors mounted at the position proximate to and below the umbilicus, as taught by Patel, for the purpose of measuring posture (para. [0074]).
Bennett-Guerrero is silent regarding the at least first motion sensor positioned corresponding to the midline of the anterior portion of the subject.
However, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, Bennett-Guerrero, and Patel, by positioning the at least first motion sensor corresponding to the midline of the anterior portion of the subject, because such a modification would have been obvious to try since there are finite potential locations to place the motion sensor to measure upper body posture with a reasonable level of success and one of ordinary skill in the art could have pursued the known potential location with a reasonable expectation of success.
Re Claims 28 and 30, Kacyvenski discloses an article, comprising:
a shirt configured to be worn on an upper body of a subject (para. [0205], form-fitting apparel including, but not limited to shirts or sporting apparel);
a plurality of sensors, including a plurality of motion sensors, mounted to the shirt for providing subject data, wherein the plurality of motion sensors are configured and arranged to provide subject data characteristic of sufficient features associated with the upper body of the subject, including at least one feature associated with movement of the upper body of the subject, to determine a subject breathing event (para. [0205], conformal sensor devices, para. [0212], The example conformal sensor devices herein include one or more sensor components, such as but not limited to triaxial accelerometers and/or gyroscopes, that can be implemented to measure the body mechanics during the throwing action and over a series of throwing sessions; para. [0259], EMG and accelerometer to measure respiratory rhythms and movement),
a data transfer structure on the shirt coupled to the plurality of sensors and configured to facilitate transferring the subject data off of the shirt (para. [0016], conformal sensor device include at least one stretchable interconnect to electrically couple the at least one sensor component to a transmitter, a transceiver, and a memory; para. [0044], at least one communication interface to transmit the data indicative of the at least one measurement and/or the indication of the performance of the individual; para. [0086], measurement data may be transmitted to an external computing device and/or the cloud).
Kacyvenski further discloses that the shirt includes a chest zone, an upper abdomen zone, a lower abdomen zone, a left arm zone and a right arm zone (para. [0205], form-fitting apparel including, but not limited to shirts, sporting apparel), and the plurality of motion sensors includes one or more motion sensors on each of the chest zone (para. [0089], [0095], [0167], motion sensor on chest or various portions of a torso), abdomen zone (para. [0089], conformal sensor on abdomen; para. [0095], [0167], motion sensor on various portions of a torso), left arm zone and right arm zone (para. [0089], [0091], [0130], [0167], Table 1, motion sensor on each arm).
Kacyvenski is silent regarding wherein the breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a cough event, a sneeze event, a choke event, a low intensity talking event, normal intensity talking event, a medium intensity talking event, a high intensity talking event, a scream event, and an apnea event; wherein at least two of the plurality of motion sensors are located on the shirt at positions corresponding to a midline of an anterior portion of the subject; and wherein at least a first of the plurality of motion sensors is located on the shirt at a position corresponding to a position proximate to and above an umbilicus of the subject, and at least a second of the plurality of motion sensors is located on the shirt at a position corresponding to a position proximate to and below the umbilicus of the subject; the plurality of motion sensors include one or more sensors on each of upper abdomen zone and lower abdomen zone.
However, Murgas discloses a plurality of motion sensors configured and arranged to provide subject data characteristic of sufficient features associated with the upper body of the subject (para. [0008], the at least one motion sensor comprises one or more linear motion sensors and/or one or more angular motion sensors), including at least one feature associated with movement of the upper body of the subject to determine a subject breathing event, wherein the breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a cough event, a sneeze event, a choke event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a scream event, and an apnea event, (para. [0085], The trained machine learning system 20 can classify breathing patterns and identify breathing patterns that deviate from a reference breathing pattern(s) using the respiration measurement output 21. It can, for example, detect a breathing pattern produced by sleep apnea; para. [0080], trained neural network).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski, by configuring and arranging a plurality of motion sensors to provide subject data characteristic of sufficient features associated with the upper body of the subject, including at least one feature associated with movement of the upper body of the subject to determine a subject breathing event, wherein the breathing event is at least one of a normal intensity breathing event, a medium intensity breathing event, a high intensity breathing event, a cough event, a sneeze event, a choke event, a low intensity talking event, a normal intensity talking event, a medium intensity talking event, a high intensity talking event, a scream event, and an apnea event, as taught by Murgas, for the purpose of detecting sleep apnea by the breathing patterns (para. [0085]) and further refining the algorithm that detects sleep apnea (para. [0124]).
Murgas is silent regarding wherein at least two of the plurality of motion sensors are located on the shirt at positions corresponding to a midline of an anterior portion of the subject; and wherein at least a first of the plurality of motion sensors is located on the shirt at a position corresponding to a position proximate to and above an umbilicus of the subject, and at least a second of the plurality of motion sensors is located on the shirt at a position corresponding to a position proximate to and below the umbilicus of the subject; the plurality of motion sensors include one or more sensors on each of upper abdomen zone and lower abdomen zone.
Bennett-Guerrero discloses a motion sensor located on an article (para. [0482], The sensor and/or attachment mechanism can include a material or other apparatus that is attachable to a patient's body, either directly or indirectly. Indirectly attached, such as by being attached to the patient's cloths, such as the patient's hospital gown or other article of clothing) at position corresponding to an anterior portion of the subject, proximate to and above an umbilicus of a subject, and on upper abdomen zone (para. [0199], an accelerometer is used to measure the angle of incline of the patient’s upper abdomen; para. [0480], attached incline sensor accurately measures the incline of a relevant body area (e.g., upper abdomen/chest); para. [0200], supine or prone position) for the purpose of reducing or preventing reflux and/or aspiration (para. [0216]), facilitating or ensuring adequate head of bed elevations for certain patients, such as those receiving mechanical ventilation, patients being enterally fed (para. [0199]) and monitoring sleep position and detecting sleep apnea (para. [0200]; para. [0098], 1) to diagnose sleep-related conditions, including but limited to sleep apnea, 2) determining whether a patient is asleep or awake for the purpose of setting parameters relating to respiration, heart rate, etc. However, other embodiments include sensor(s) and/or sensor system(s) that can be applied in the context of monitoring other aspects of, or conditions directly or indirectly related to, sleep, including but not limited to duration, position, movements, quality, etc.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, by adding a motion sensor located on the article at position corresponding to an anterior portion of the subject, wherein at least a first of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and above an umbilicus of the subject and on upper abdomen zone, as taught by Bennett-Guerrero, for the purpose of reducing or preventing reflux and/or aspiration (para. [0216]), facilitating or ensuring adequate head of bed elevations for certain patients, such as those receiving mechanical ventilation, patients being enterally fed (para. [0199]), monitoring sleep position and detecting sleep apnea (para. [0200]; para. [0098]).
Bennett-Guerrero is silent regarding wherein a second sensor located on the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and below the umbilicus of the subject and on lower abdomen zone.
However, Patel discloses a second sensor located on the article (para. [0011], The wearable electronic device can be adhered to the body by an adhesive or positioned against the body by straps or clothing) at position corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is mounted to the article at a position corresponding to a position proximate to and below the umbilicus of the subject and lower abdomen zone (fig. 3, ref# 303e).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas and Bennett-Guerrero, by adding a second sensor located on the article at positions corresponding to a midline of an anterior portion of the subject, wherein at least a second of the plurality of motion sensors is located on the article at a position corresponding to a position proximate to and below the umbilicus of the subject and on lower abdomen zone, as taught by Patel, for the purpose of measuring posture (para. [0074]).
Bennett-Guerrero is silent regarding the at least first motion sensor positioned corresponding to the midline of the anterior portion of the subject.
However, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, Bennett-Guerrero, and Patel, by positioning the at least first motion sensor corresponding to the midline of the anterior portion of the subject, because such a modification would have been obvious to try since there are finite potential locations to place the motion sensor to measure upper body posture with a reasonable level of success and one of ordinary skill in the art could have pursued the known potential location with a reasonable expectation of success.
Re Claim 10, Kacyvenski discloses that processing the data comprises:
converting at least portions of the data into context data associated with human-relatable values (Table 1, flexor/extensor data. Measure of muscle tension during dynamic stretching. Confirming user movement patterns with those of professionals (such as but not limited to Swing in golf putting, face-off in hockey, Swing and pitch in baseball, punt in football, corner kicks in Soccer, etc. Detection of kinetic link - the order in which muscles or muscle groups are being fired - assisting on desired patterns to improve movement speed and accuracy.); and
processing the context data (Table 1, Muscle activity and motion as means to baseline symmetry (Table 1, diagnosis of possible need to balance flexor extensor symmetry - prevention of musculoskeletal injuries caused by imbalances. Detect desired ranges and motion patterns for each athlete based on muscle response and activity - maximizing the quality of stretching, and minimizing injuries. compare his/her movement or performance with, e.g., an athlete or other famous person, with user athlete person consent. Detection of kinetic link - the order in which muscles or muscle groups are being fired - assisting on desired patterns to improve movement speed and accuracy.).
Re Claim 11, Kacyvenski discloses that
receiving the data includes receiving data from each of at least two zones of the article (para. [0089], at least one conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen, the shoulder, and/or an arm of the individual; para. [0205], The conformal sensor devices described herein can be attached to the body as a sticker or incorporated into form-fitting apparel including shirts; para. [0167], torso and arms); and
processing the data includes processing the data from the at least two zones (para. [0212], The example conformal sensor devices include triaxial accelerometers and/or gyroscopes, that can be implemented to measure the body mechanics during the throwing action and over a series of throwing sessions. The example conformal sensor devices facilitate flexible placement methods, and therefore so can be placed on any portion of the body, including the hand, wrist, forearm, upper arm, shoulder, or any other applicable body part; para. [0167], determining a kinetic link for swinging an object using conformal sensors on torso and arms; para. [0130], tilt or inclination; para. [0259], fig. 25, Example conformal sensor system 2502 can be disposed on or otherwise coupled to the thoracic diaphragm, to measure respiratory rhythms and movement; Table 1, Breathing event during sleep using accelerometer and EMG: Motion may detect respiratory rhythms, amount of movement in bed and how many times the person wakes up/stands up to go to the bathroom, or get water. Muscle activity may indicate relaxation level and indicate bruxism. – location of accelerometer reads on first zone of the article and location of EMG reads on second zone of the article.).
Re Claim 12, Kacyvenski discloses that receiving the data comprises receiving the data from the plurality of sensors mounted to a shirt (para. [0205], The conformal sensor devices described herein can be attached to the body as a sticker or incorporated into form-fitting apparel including shirts).
Re Claim 13, Kacyvenski discloses that processing the data includes identifying features associated with movement of one or more of the subject's chest, upper abdomen, lower abdomen, left arm or right arm (para. [0089], at least one conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen, the shoulder, and/or an arm of the individual; para. [0212], The example conformal sensor devices facilitate flexible placement methods, and therefore so can be placed on any portion of the body, including the hand, wrist, forearm, upper arm, shoulder, or any other applicable body part; Table 1 lists different types of features from using accelerometer and EMG).
Re Claim 14, Kacyvenski discloses that processing the data includes identifying breathing event features (para. [0259], conformal sensor system 2502 can be disposed on or otherwise coupled to the thoracic diaphragm, to measure respiratory rhythms. Table 1, respiratory rate sensing).
Re Claim 17, Kacyvenski discloses that the plurality of motion sensors comprises one or more motion sensors in each of at least two zones (para. [0089], at least one conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen, the shoulder, and/or an arm of the individual; para. [0205], The conformal sensor devices described herein can be attached to the body as a sticker or incorporated into form-fitting apparel including shirts; para. [0212], The example conformal sensor devices include triaxial accelerometers and/or gyroscopes, that can be implemented to measure the body mechanics during the throwing action and over a series of throwing sessions. The example conformal sensor devices facilitate flexible placement methods, and therefore so can be placed on any portion of the body, including the hand, wrist, forearm, upper arm, shoulder, or any other applicable body part; para. [0167], determining a kinetic link for swinging an object using conformal sensors on torso and arms; para. [0130], tilt or inclination).
Re Claim 18, Kacyvenski discloses that the article comprises a shirt and the at least two zones include zones from a group including a chest zone, an upper abdomen zone, a lower abdomen zone, a left arm zone and a right arm zone (para. [0205], The conformal sensor devices described herein can be attached to the body as a sticker or incorporated into form-fitting apparel including shirts; para. [0089], at least one conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen, the shoulder, and/or an arm of the individual).
Re Claim 26, Kacyvenski discloses that the computer system identifies the breathing event at least in part by:
converting at least portions of the subject data into context data associated with human-relatable values; and
processing the context data (para. [0259], fig. 25, Example conformal sensor system 2502 can be disposed on or otherwise coupled to the thoracic diaphragm, to measure respiratory rhythms and movement; Table 1, Breathing event during sleep using accelerometer and EMG: Motion may detect respiratory rhythms, amount of movement in bed and how many times the person wakes up/stands up to go to the bathroom, or get water. Muscle activity may indicate relaxation level and indicate bruxism. – motion data are processed to detect different features such as respiration, movement while lying down, movement while awake, standing up, and walking based on the disclosure).
Re Claim 27, Kacyvenski discloses that the computer system identifies the breathing event at least in part based upon subject data from each of at least two zones of the article; and processing the data from the at least two zones (para. [0259], fig. 25, Example conformal sensor system 2502 can be disposed on or otherwise coupled to the thoracic diaphragm, to measure respiratory rhythms and movement; Table 1, Breathing event during sleep using accelerometer and EMG: Motion may detect respiratory rhythms, amount of movement in bed and how many times the person wakes up/stands up to go to the bathroom, or get water. Muscle activity may indicate relaxation level and indicate bruxism. – location of accelerometer reads on first zone of the article and location of EMG reads on second zone of the article.).
Re Claim 29, Kacyvenski discloses that the plurality of motion sensors includes one or more sensors on at least two zones of the shirt (para. [0212], accelerometer and gyroscopes placed on hand, wrist, forearm, upper arm, shoulder, or any other applicable body part; para. [0089], conformal sensor device can be disposed on or otherwise coupled to a portion of a calf, a knee, a thigh, a head, a foot, the chest, the abdomen, the shoulder, and/or an arm of the individual)
Claims 4, 5, 22, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Kacyvenski (US 2015/0019135) as modified by Murgas (US 2021/0113114), Bennett-Guerrero (US 2015/0257654A1), and Patel (US 2016/0249174A1), and further in view of Amurthur (US 2009/0076405A1).
Re Claims 4, 5, 22, and 23, Kacyvenski as modified by Murgas, Bennett-Guerrero, and Patel discloses the claimed invention substantially as set forth in claims 1, 2, and 3 and 16, 20, and 21 respectively.
However, Kacyvenski is silent regarding the stored breathing event data is representative of one or more upper body poses and the stored breathing event data includes data received during a static upper body pose.
However, Amurthur discloses respiratory monitoring device (abstract) and teaches stored breathing event data is representative of one or more upper body poses and the stored breathing event data includes data received during a static upper body pose (para. [0125], [0126], By way of illustration, orthopnea, or paroxysmal nocturnal dyspnea (“PND”) of a patient is monitored. The processor 20 compares at least two respiration patterns. The non-recumbent respiration pattern shows that the patient is taking relatively slow and deep breaths as can be seen by the relatively low frequency and high amplitude of the pattern. However, the recumbent respiration pattern shows that the patient is taking relatively rapid and shallow breaths as indicated by the relatively high frequency and low amplitude of the pattern. The rapid and shallow breathing of the recumbent respiration pattern indicates a patient suffering from orthopnea that eventually occurs upon lying down.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, Bennett-Guerrero, and Patel, by using the stored breathing event data that is representative of one or more upper body poses and the stored breathing event data including data received during a static upper body pose, as taught by Amurthur, for the purpose of detecting the presence of orthopnea (para. [0125], [0126]).
Claims 6 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Kacyvenski (US 2015/0019135) as modified by Murgas (US 2021/0113114), Bennett-Guerrero (US 2015/0257654A1), Patel (US 2016/0249174A1), and Amurthur (US 2009/0076405A1), and further in view of Shalon (US 2006/0064037A1).
Re Claims 6 and 24, Kacyvenski as modified by Murgas, Bennett-Guerrero, Patel, and Amurthur discloses the claimed invention substantially as set forth in claim 1, 2, 3, 4, and 5 and claims 16, 20, 21, 22, and 23, respectively.
Kacyvenski, Murgas, Bennett-Guerrero, Patel, and Amurthur are silent regarding the stored breathing event data includes data received during a dynamic upper body pose.
However, Shalon discloses a health monitoring device (abstract) and teaches stored breathing event data includes data received during a dynamic upper body pose (para. [0301], system 10 can use the acoustic energy signatures of the user's breathing or heartbeat to determine whether the user is complying with the workout plan. If, for example, the user is running, system 10 can hear the user's breathing patterns to determine workout intensity. If, for example, the user is lifting weights, system 10 can use the acoustic energy signature of the regular pattern of exhales between each exertion as a sign that the user is actually lifting a weight according to the training plan.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Kacyvenski as modified by Murgas, Bennett-Guerrero, Patel, and Amurthur, by configuring the stored breathing event data to include data received during a dynamic upper body pose, as taught by Shalon, for the purpose of determining whether the user is complying with the workout plan (para. [0301]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VYNN V HUH whose telephone number is (571)272-4684. The examiner can normally be reached Monday to Friday from 9 am to 5 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin Klein can be reached at (571) 270-5213. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JONATHAN T KUO/Primary Examiner, Art Unit 3792
/V.V.H./
Vynn Huh, June 1, 2026Examiner, Art Unit 3792
Prosecution Insights