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 .
Priority
The instant application claims priority to provisional application 63/249,263 and as such the earliest priority date of 09/28/2021 has been granted to the instant application.
Response to Amendment
The amendments have been sufficient to overcome the original claim objections and rejections under 35 USC 112(b) presented in the previous Final Action.
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 1-5, and 7-9 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.
Claim 1 recites the limitation “a first computer program code” on line 16. It is unclear if this first program code is part of, or separate than, the at least one computer program code claimed previously on line 12.
Furthermore, claim 1 recites the limitation “wherein a first program code is configured to create a 3-dimensional model of the foreign object” on lines 16-17. It is unclear if this 3-dimensional model of the foreign object is the same as the 3-D model claimed previously on lines 8-9. In addition, the examiner notes that the acronym 3-D on line 8 has not been defined in the claim yet and suggests fully expanding it to 3-dimensional in all instances.
Claim 2 recites the limitation “a second program code” on line 2. It is unclear if the second program code is part of, or separate than, the at least one computer program code claimed previously on line 12 of claim 1. The examiner suggests amending claim 1 to be similar to --at least one computer program code including a first and second computer program code…--
Claim 3 recites the limitation “a third program code” on line 2. It is unclear if the third program code is part of, or separate than, the at least one computer program code claimed previously on line 12 of claim 1. The examiner suggests amending claim 1 to be similar to --at least one computer program code including a first and second computer program code…--
Claim 4 recites the limitation “a fourth program code” on line 2. It is unclear if the fourth program code is part of, or separate than, the at least one computer program code claimed previously on line 12 of claim 1. The examiner suggests amending claim 1 to be similar to --at least one computer program code including a first and second computer program code…--
Claim 7 recites the limitation “wherein the outcome consists of causing an apparatus for generating a deformation model of at least one finger resistance device to perform” on line 1-3. It is unclear how many devices are required for the invention, as claim 6 established “a method for acquiring haptic data from an ergonomic rectangle-shaped device with rounded edges”, and therefore it is unclear if the new apparatus of claim 7 and the new at least one finger resistance device are the same as the claimed ergonomic rectangle-shaped device in claim 6, or if they are three separate structures where the ones in claim 7 are controlled by the device of claim 6. The examiner notes that neither the specification of the instant application, nor the drawings, support multiple devices controlled by main device and only discuss a single handheld finger training device used in the system, which if clarified to be multiple devices will cause further drawing objections and possible new matter rejections under 35 USC 112(a) to be made.
Dependent claims 2-5, and 8-9 are rejected due to their dependency on a rejected base claim.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 6 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Silagy et al. US 20150190675 A1.
Regarding claim 6:
Silagy discloses a method for acquiring haptic data from an ergonomic rectangle-shaped device with rounded edges (“Advantageously, the contours of thumb saddle 47 and finger saddle 48 enable a user to grasp finger exerciser 30 in a manner which enables the targeted exercise to be performed ergonomically and which may provide improved physiological benefits.” See paragraph [0069] and figure 2) that is designed to be manipulated with one hand (See figure 10b) and displaying results (“Handheld device 73 includes an application program ("app") that is programmed to collect and display the spatial and positional exercise data.” See paragraph [0067]) comprising: a non-transitory computer-readable storage medium(“Controller 13 includes a microprocessor 26 (FIG. 1a) configured to execute a set of programmed instructions which is stored in memory 27, such as non-transitory memory, included in controller 13.” See paragraph [0056]),one or more sequences of one or more instructions (See previous citation of paragraph [0056]), one or more processors (microprocessor 26), wherein the non-transitory computer-readable storage medium carrying the one or more sequence of the one or more instruction which, when executed by the one or more processors, causes an outcome (The examiner notes this limitation is merely reciting the function of a controller with a processor executing its main function).
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Claim Rejections - 35 USC § 103
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.
Claim(s) 1-5,and 7-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Silagy et al. US 20150190675 A1, and further in view of Raghavan et al. US 20160067136 A1.
Regarding claim 1:
Silagy teaches a hand training device (Finger exerciser 30) comprising: a body (See fig 2), a housing (Housing 31), at least one finger resistance device (compression spring 16), at least one processor (microprocessor 26), and at least one memory (memory 27) configured to: store at least one computer program code (“Controller 13 includes a microprocessor 26 (FIG. 1a) configured to execute a set of programmed instructions which is stored in memory 27, such as non-transitory memory, included in controller 13.” See paragraph [0056]).
[AltContent: textbox (Hand training device (finger trainer) with housing)][AltContent: arrow]
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[AltContent: textbox (Internal view showing resistive springs)][AltContent: arrow]
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Silagy fails to teach at least one capacitive sensor, wherein the at least one capacitive sensor is used to measure a force applied to the hand training device, determine a foreign object position, and collected data from the capacitive sensor is used to create a 3-D model of the foreign object, and that the at least one computer program code is configured to: with the at least one processor to cause the hand training device to apply at least one electronic charge to the at least one capacitive sensor, and measure a capacitance of the at least one capacitance sensor; wherein a first program code is configured to create a 3- dimensional model of the foreign object based on the measured capacitance of the at least one capacitive sensor, when the at least one capacitance sensor is affected by the foreign object.
Raghavan, however, teaches a game-based sensorimotor rehabilitator that enables individuals to interact with the functional objects using the appropriate amount of force, tilt, finger movement, and muscle activity to regain lost skill due to injury (See abstract), and further teaches at least one capacitive sensor (Paragraph [0110] states that the device 2010 can use buttons, manual mechanisms, or can be automatically initialized through the use of capacitive sensors) , wherein the at least one capacitive sensor is used to measure a force applied to the hand training device (The examiner notes that in order for the capacitive sensor to initialize the device it must measure a force of the user’s finger on the sensor), determine a foreign object position, and collected data from the capacitive sensor is used to create a 3-D model of the foreign object (“In one implementation, real objects are customized with force, orientation and acceleration sensors and the object is virtualized on screen. As the individual manipulates the object or objects, visual feedback is provided regarding the appropriateness of fingertip forces, and orientation in a systematic manner to facilitate learning of the correct associations. The force and orientation information is also fed to computational biomechanical models, and software algorithms to inform the thresholds for visual feedback.” See paragraph [0056] and figures 6A-6C which are virtual depictions of a hand grasping a cylinder as a result of the collected data from the various sensors used in the training device and the corresponding mapping of hand joints to the detected forces/capacitance), and that the at least one computer program code is configured to: with the at least one processor to cause the hand training device to apply at least one electronic charge to the at least one capacitive sensor, and measure a capacitance of the at least one capacitance sensor (“For the given circuit, we measure the charge/discharge time of the capacitor and correlate that to the flexi-force resistance, which in turn in correlated to the amount of force applied on it.” See paragraph [0035]); wherein a first program code is configured to create a 3- dimensional model of the foreign object based on the measured capacitance of the at least one capacitive sensor (The examiner notes that due to the unclear nature of the claim language, see 35 USC 112(b) rejection above, the second claimed 3-dimensional image generated by the computer program code is being considered under the broadest reasonable interpretation with no further structural or functional limitations as the same 3-D model of the foreign object discussed above and therefore these limitations recite the same functions merely reworded and are thereby rejected under the same rational discussed with paragraph [0056] above), when the at least one capacitance sensor is affected by the foreign object (“The grip force (normal contact force) exerted by each finger, measured by the force sensors, will be used to map to the joint space in a computational hand/arm model, which will output the joint torque at each finger joint (each finger has 3 joints: the distal PIP, proximal PIP, and MCP).” See paragraph [0073]).
Furthermore, Raghavan teaches measuring and generating a result of the pinch strength detected (“Subjects also showed clinical improvement in tactile sensibility, higher order sensory integration (stereognosis and 2-point discrimination), pinch strength, timing on fine motor tasks (8-13) of the Wolf Motor Function Test and quality of life measured with the Stroke Impact Scale (Table 2).” See paragraph [0099]).
[AltContent: textbox (-FIG. 6A is an image of a virtual human grasping a cylinder,
-FIG. 6B is a schematic of a finger grasping a cylinder;
-FIG. 6C is a schematic mapping the joints of a hand.
See paragraph [0017])]
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It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the hand trainer of Silagy to include at least one capacitive sensor, and the capability to detect and report grip strength and pinch strength to the user, with a 3-dimensional depiction of a foreign object appearing to move or deform based on the collected force/capacitive data as taught by Raghavan, since this would allow the system to provide a visual output in addition to the tactile one to provide feedback with the remote devices, and would provide more accurate feedback beyond just the user knowing if they successfully compressed the resistive springs, furthering their training and allowing them to make progress more quickly.
Regarding claim 2:
Silagy as modified by Raghavan teaches the hand training device of claim 1, further comprising the at least one computer program code is configured to: create a deformation model that is generated when there is change in the measured capacitance of the at least one capacitive sensor (The examiner notes that paragraph [0073] discusses the graphs depicted in figure 7 of Raghavan where the paragraph states that the forces detected by the sensors as the fingers exert forces, such as through squeezing the virtual cups/balls etc., map the forces of each joint to the modeled hand and therefore as depicted in figure 7 the forces ramping up or down during the exercise area deformation model due to the user squeezing the controller.)
Silagy as modified by Raghavan fails to specifically teach a second program code. However, the examiner notes that due to the unclear nature of the claim language, see 35 USC 112(b) rejection above, whether the second program code is a completely separate code or a part of the overall at least one computer program code of claim 1 is unclear, and additionally, that having another computer code amounts to no more than a mere duplication of parts as having multiple sections of code, or multiple codes, in a programmed device each executing various functions is known in the art and would have been obvious to a person of ordinary skill in the art to modify the invention taught by the combination of Silagy and Raghavan to include a second program code.
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Regarding claim 3:
Silagy as modified by Raghavan teaches the hand training device of claim 1, further comprising the at least one computer program code is configured to: provide one or more result indicating a grip strength exerted by the foreign object in at least one axis and provides the one or more result as an output (The examiner notes that as stated above in claim 1 Raghavan outputs the results of the forces detected by the sensors from the users fingers, and further specifies how they are used to provide outputs of joint torques etc. as stated in paragraph [0073] where it states, (“The grip force (normal contact force) exerted by each finger, measured by the force sensors, will be used to map to the joint space in a computational hand/arm model, which will output the joint torque at each finger joint (each finger has 3 joints: the distal PIP, proximal PIP, and MCP).” See paragraph [0073]).
Silagy as modified by Raghavan fails to specifically teach a third program code. However, the examiner notes that due to the unclear nature of the claim language, see 35 USC 112(b) rejection above, whether the third program code is a completely separate code or a part of the overall at least one computer program code of claim 1, is unclear, and additionally, that having another computer code amounts to no more than a mere duplication of parts as having multiple sections of code, or multiple codes, in a programmed device each executing various functions is known in the art and would have been obvious to a person of ordinary skill in the art to modify the invention taught by the combination of Silagy and Raghavan to include a third program code.
Regarding claim 4:
Silagy as modified by Raghavan teaches the hand training device of claim 1, further comprising the at least one computer program code, is configured to: provide one or more results indicating a pinch strength exerted by the foreign object in at least a one axis (See rejection of claim 1) and provides the one or more result as an output (See rejection of claim 1).
Silagy as modified by Raghavan fails to specifically teach a fourth program code. However, the examiner notes that due to the unclear nature of the claim language, see 35 USC 112(b) rejection above, whether the fourth program code is a completely separate code or a part of the overall at least one computer program code of claim 1, is unclear, and additionally, that having another computer code amounts to no more than a mere duplication of parts as having multiple sections of code, or multiple codes, in a programmed device each executing various functions is known in the art and would have been obvious to a person of ordinary skill in the art to modify the invention taught by the combination of Silagy and Raghavan to include a fourth program code.
Regarding claim 5:
Silagy as modified by Raghavan teaches the hand training device of claim 1, wherein the at least one capacitive sensor comprises two or more capacitive sensors (As noted in the rejection of claim 1 above, Raghavan states that multiple capacitive sensors can be used to measure the force and initialize the machine, and that there are multiple resistor-capacitor force sensors throughout the device) and the at least one processor is configured to generate a 3-dimensional model of a foreign object based on the measured capacitance of the two or more capacitive sensors and the distance between the two or more capacitance sensors (See rejection of claim 1).
Regarding claim 7:
Silagy teaches the method from claim 6, but fails to teach wherein the outcome consists of causing an apparatus for generating a deformation model of at least one finger resistance device to perform: retrieving a one or more capacitive sensor data, wherein the one or more capacitive sensor data indicates the position of a foreign object or a change in position of the foreign object, processing the one or more capacitive sensor data to create a 3-dimensional model of the foreign object, and generating a deformation model of the at least one finger resistance device based on the 3-dimensional model of the foreign object to obtain a result.
Raghavan, however, teaches a game-based sensorimotor rehabilitator that enables individuals to interact with the functional objects using the appropriate amount of force, tilt, finger movement, and muscle activity to regain lost skill due to injury, and further teaches wherein the outcome consists of causing an apparatus for generating a deformation model of at least one finger resistance device The examiner notes that due to the unclear nature of the claim language, see 35 USC 112(b) above, as there is no support in the drawings or specification for a second apparatus in the system other than the single finger resistive device and a display, the claimed limitation is being considered under the broadest reasonable interpretation with no further structural or functional limitations as the same ergonomic rectangle-shaped device with rounded edges claimed in independent claim 6) to perform, retrieving a one or more capacitive sensor data (Paragraph [0110] of Raghavan discusses various sensor types which can be used to initialize the device, and specifically states using capacitive sensors, which would inherently include a step of retrieving sensor data as the device detects the use of the capacitive sensors) wherein the one or more capacitive sensor data indicates the position of a foreign object or a change in position of the foreign object (The examiner notes that paragraph [0035] discusses how the force sensors use the capacitance to detect the forces applied to the device where it states, “For the given circuit, we measure the charge/discharge time of the capacitor and correlate that to the flexi-force resistance, which in turn in correlated to the amount of force applied on it. This circuit is used to measure the force applied (load force and grasping forces).” With paragraph [0058] further specifying that the force sensors are used to detect the position of the fingers and palm on the device where it states, “Force sensors 303, such as force sensitive resistors, are positioned to correspond with a user's hand. For example, the force sensors may be positioned at multiple locations to correlate with fingertip and palm placement on the game controller 301.”), processing the one or more capacitive sensor data to create a 3-dimensional model of the foreign object, and generating a deformation model of the at least one finger resistance device based on the 3-demensional model of the foreign object to obtain a result (“In one implementation, real objects are customized with force, orientation and acceleration sensors and the object is virtualized on screen. As the individual manipulates the object or objects, visual feedback is provided regarding the appropriateness of fingertip forces, and orientation in a systematic manner to facilitate learning of the correct associations. The force and orientation information is also fed to computational biomechanical models, and software algorithms to inform the thresholds for visual feedback.” See paragraph [0056] and figures 6A-6C which are virtual depictions of a hand grasping a cylinder as a result of the collected data from the various sensors used in the training device and the corresponding mapping of hand joints to the detected forces/capacitance).
Furthermore, Raghavan teaches the device measuring and generating a result of the grip strength detected (“The grip force (normal contact force) exerted by each finger, measured by the force sensors, will be used to map to the joint space in a computational hand/arm model, which will output the joint torque at each finger joint (each finger has 3 joints: the distal PIP, proximal PIP, and MCP).” See paragraph [0073]), and device measuring and generating a result of the pinch strength detected (“Subjects also showed clinical improvement in tactile sensibility, higher order sensory integration (stereognosis and 2-point discrimination), pinch strength, timing on fine motor tasks (8-13) of the Wolf Motor Function Test and quality of life measured with the Stroke Impact Scale (Table 2).” See paragraph [0099]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Heath to include generating a 3-dimensional model based on the processed sensor data as taught by Raghavan as the deformation model is already present and provides visual feedback in a two dimensional from, so adding a 3-dimension image for the user to see the forces they exert would add to the feedback of their training and allow them to understand better where they need to apply, or lessen the forces on the device, and how to better optimize their training.
Regarding claim 8:
Silagy as modified by Raghavan teaches the method of claim 7, wherein the result indicates a grip strength exerted by the hand in at least one axis (See rejection of claim 7).
Regarding claim 9:
Silagy as modified by Raghavan teaches the method of claim 7, wherein the result indicates a pinch strength exerted by the hand in the at least one axis (See rejection of claim 7).
Regarding claim 10:
Silagy teaches the method of claim 6, wherein the outcome consists of causing an apparatus to detect, in real-time by the at least one capacitive sensor, a position of a hand and a change in the position of the hand in at least one axis (“During use, data relating to an exercise being performed is received by a controller. In the example embodiment shown in FIG. 8, positional motion of a finger exerciser 70 is sensed by spatial sensor 74 (accelerometer, gyroscope, compass, etc.) and communicated to a controller 76. ” See paragraph [0067]).
Silagy fails to teach generating a 3-dimensional shape of the hand based on the detected position, and detected change of position of the hand; and measure a deformation of the at least one finger resistance device to obtain a result.
Raghavan, however, teaches a game-based sensorimotor rehabilitator that enables individuals to interact with the functional objects using the appropriate amount of force, tilt, finger movement, and muscle activity to regain lost skill due to injury, and further teaches generating a 3-dimensional shape of the hand based on the detected position (See figures 6A-6C), and detected change of position of the hand (See figures 6A-6C); and measure a deformation of the at least one finger resistance device to obtain a result (“The grip force (normal contact force) exerted by each finger, measured by the force sensors, will be used to map to the joint space in a computational hand/arm model, which will output the joint torque at each finger joint (each finger has 3 joints: the distal PIP, proximal PIP, and MCP).” See paragraph [0073]), and further teaches measuring and generating a result of the pinch strength detected (“Subjects also showed clinical improvement in tactile sensibility, higher order sensory integration (stereognosis and 2-point discrimination), pinch strength, timing on fine motor tasks (8-13) of the Wolf Motor Function Test and quality of life measured with the Stroke Impact Scale (Table 2).” See paragraph [0099]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Silagy to include generating a 3-dimensional model based on the processed sensor data as taught by Raghavan as the deformation model is already present and provides visual feedback in a two dimensional from, so adding a 3-dimension image for the user to see the forces they exert would add to the feedback of their training and to have the results be indicative of the grip strength and pinch strength of the users hand would allow them to track their progress as they exercise with actual force values in addition to the virtual representations.
Regarding claim 11:
Silagy as modified by Raghavan teaches the method of claim 10, wherein the result indicates a grip strength exerted by the hand in at least one axis (See rejection of claim 10).
Regarding claim 12:
Silagy as modified by Raghavan teaches the method of claim 10, wherein the result indicates a pinch strength exerted by the hand in at least one axis (See rejection of claim 10).
Response to Arguments
Applicant's arguments filed 02/17/2026 have been fully considered but they are not persuasive.
With respect to the arguments in regards to the previous rejection of independent claim 6 under 35 USC 102(a)(1) in view of the Heath reference, the examiner notes that due to the amended claim limitations a new search and consideration, and as a result a new rejection in view of the Silagy reference as presented above was required which as noted above discloses the newly added limitations.
In regards to the arguments presented with respect to the rejection of claims 1-5 under 35 USC 103 in view of the combination of the Silagy and Raghavan references the examiner respectfully disagrees. Raghavan does disclose using capacitive sensors to initialize the device, which is the capacitive sensors detecting and measuring a force as the system must recognize the intentional pressure exerted by the user on the sensor in order to issue the command to wake up. Furthermore, Raghavan discusses throughout the disclosure the use of resistor-capacitor sensors as the force sensors of the device which are used by the system to measure the forces and placement of the users fingers and hand during use, which causes the system to generate the 3-dimensional models, and virtual game controls discussed throughout as noted in the rejections above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN ANGELO DICUIA whose telephone number is (703)756-4713. The examiner can normally be reached M-F 7:30-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, LoAn Jimenez can be reached at (571) 272-4966. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.A.D./Examiner, Art Unit 3784
/Megan Anderson/Primary Examiner, Art Unit 3784