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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on January 22, 2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings filed on November 19, 2024 are accepted.
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 37-53 and 81-82 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 pre-AIA the applicant regards as the invention.
Claims 37, 53 and 81 recites “…to detect a muscle movement from the spectrophotometric representation after isolating a component of the optical property signal corresponding to a heartbeat from the received optical property signal” that renders the scope of the claims indefinite. It is unclear whether the isolation of the heartbeat component participates in the detection of the muscle movement, or it merely states a timing condition of the muscle movement detection. Note that in claim 53, the claim recites “to isolate a signal corresponding to a heartbeat from the optical property signal and to distinguish muscle movements corresponding to one or more muscles based on the received optical property signals”, in which the signal isolation and the muscle movement distinguishment are recited as two independent steps without any link in between. The “received optical signal” refers to line 11, the signal received from the optical detectors, hence still comprises the signal corresponding to the heartbeat.
Alternatively, if Applicant intends to recite that the isolation step participates in the detection of the muscle movement, it is unclear in regard to what kind of role it plays – whether the muscle movement is detected solely based on the isolated signal, or the muscle movement is detected without the isolated signal (with the isolated signal removed from the received signal). Please also see below the rejection to claim 39.
Claim 39 recites “the processor is configured to isolate the component of the optical property signal corresponding to the heartbeat to detect a muscle movement” that renders the scope fo the claim indefinite. It is unclear what role this isolation step plays in the detection of the muscle movement. It is unclear whether (1) the heartbeat component is isolated, i.e., identified and extracted, and the extracted heartbeat component is used to detect the muscle movement, or (2) the heartbeat component is isolate, i.e., identified and extracted, and removed from the optical property signal, and the optical property signal with the heartbeat component removed is used for the muscle movement detection. For examination purpose, according to the specification, claims 37, 39, 53 and 81 are interpreted to be (2) although claim 39 by plain English means (1). Clarification with proper amendment is required. Each step that that processor performs to arrive the muscle movement detection should be explicitly recited.
Claims 39, 48 and 50 recites “(a) muscle movement”. It is unclear whether it refers to the same as the identical term recited in claim 37, line 8. Proper antecedent basis is required if they refer to the same.
Claims 38 and 81 recite “the registration” that lacks proper antecedent basis.
Claim 82: “the anatomical features” lacks proper antecedent basis.
The dependent claims of the above rejected claims are rejected due to their dependency.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 37, 39-47 and 50-53 are rejected under 35 U.S.C. 103 as being unpatentable over Connor et al., US 2025/0134381 A1, hereinafter Connor, in view of Currà et al., “Near-infrared spectroscopy as a tool for in vivo analysis of human muscles” Scientific Reports. 2019, 9:8623, hereinafter Currà, further in view of Tscharner et al., “ Removal of the electrocardiogram signal from surface EMG recordings using non-linearly scaled wavelets”. Journal of Electromyography and Kinesiology. 21 (2011) 683-688, hereinafter Tscharner.
Claims 37 and 53. Connor teaches in FIGS.1-4 a wearable system for detecting neuromuscular activity, the system comprising:
a spectrophotometric sensor set comprising an array of spectrophotometric sensors wherein each spectrophotometric sensor is configured to detect an optical property signal from a tissue corresponding to a spectrophotometric representation of a region of a subject's skin ([0454]: the biometric wearable device (e.g., finger ring or smart watch) can comprise: a wearable device worn around a body member (e.g., finger, wrist, and/or arm); one or more sensors on the device selected from the group consisting of motion sensor, muscle function monitor, near-infrared spectroscopic (e.g., optical) sensor…., optical sensor; [0437]: heart rate sensor…, PPG sensor…an arcuate array of light emitters around the wearable device, wherein a selected subset of the light emitters are activated to emit light at a given time based on data from the one or more sensors; and one or more light receivers which receive light beams from the light emitters after the light beams have been transmitted through or reflected by the body member; and [0439]: a circumferential array of light emitters around the wearable device, wherein light emitters in the array of light emitters emit light beams with spectral ranges, frequencies, and/or colors which vary over time);
a support configured to hold the spectrophotometric sensor adjacent to a skin surface ([0454]: the biometric wearable device (e.g., finger ring or smart watch) can comprise: a wearable device worn around a body member (e.g., finger, wrist, and/or arm); FIGS.1-4); and
a processor configured to receive the spectrophotometric representation from the spectrophotometric sensor set ([0478]: a biometric wearable device…can further comprise a local data processor…a biometric wearable device…can include a data transmitter which transmits data from the light receivers to a remote data processor), and
to detect a muscle movement from the spectrophotometric representation ([0454]: the biometric wearable device (e.g., finger ring or smart watch) can comprise:…one or more sensors on the device selected from the group consisting of motion sensor, muscle function monitor, near-infrared spectroscopic (e.g., optical) sensor).
Connor teaches a muscle function monitor and a near-infrared spectroscopic sensor. However, Connor does not teach that the muscle function monitor is performed by a spectrophotometric sensor set, and the near-infrared spectroscopic sensor is used for detecting muscle movements.
However, in an analogous near IR spectroscopic sensor-based muscle movement detection field of endeavor, Currà teaches such a feature in Abstract: near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo. In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (i.e., “fingerprints”) of upper limb flexors and extensors, which represent specific, accurate, and reproducible measures of the overall biological status of these muscles.
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system of Connor employ such a feature of “detect a muscle movement from the spectrophotometric representation” as taught in Currà for the advantage of “enables more thorough evaluation of the muscular system and optimal monitoring of the effectiveness of therapeutic or rehabilitative interventions”, as suggested in Currà, Abstract.
Neither Connor nor Currà teaches that the muscle movement is detected after isolating a component corresponding to a heartbeat from the received signal.
However, in an analogous muscle movement data processing and analysis field of endeavor, Tscharner teach
the muscle movement is detected after isolating a component corresponding to a heartbeat from the received signal (p.683: Abstract: the EMG signal recorded on some areas of the body, especially from the trunk, is often contaminated with heart muscle electrical activity (ECG) caused by the proximity of the collection sites to the heart. It is therefore necessary to suppress or separate the ECG signal from the EMG signal during the analysis; 1. Introduction, ¶-3: the purpose of this study was to develop a method to remove the ECG from the contaminated EMG signals using the non-linearly scaled wavelets mentioned above and the ICA).
As Connor and Currà combined teaches using optical sensors for measuring the muscle movement and the heartbeat, when Connor, Currà and Tscharner are combined, the isolated component is a component of the optical property signal, and the received signal is a received optical property signal, i.e., “after isolating a component of the optical property signal corresponding to a heartbeat from the received optical property signal” as claimed.
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system of Connor and Currà combined employ such a feature of “detecting the muscle movement after isolating a component corresponding to a heartbeat from the received signal” as taught in Tscharner for the advantage of removing the heartbeat component from a contaminated received signal…resulting cleaned signal retains the spectral properties required for a further time/frequency analysis, as suggested in Tscharner, p.687, last paragraph.
Claim 39. Tscharner further teaches that the processor is configured to
isolate the component corresponding to the heartbeat to detect a muscle movement (p.683: Abstract: the EMG signal recorded on some areas of the body, especially from the trunk, is often contaminated with heart muscle electrical activity (ECG) caused by the proximity of the collection sites to the heart. It is therefore necessary to suppress or separate the ECG signal from the EMG signal during the analysis; 1. Introduction, ¶-3: the purpose of this study was to develop a method to remove the ECG from the contaminated EMG signals using the non-linearly scaled wavelets mentioned above and the ICA).
As Connor and Currà combined teaches using optical sensors for measuring the muscle movement and the heartbeat, when Connor, Currà and Tscharner are combined, the isolated component is a component of the optical property signal, i.e., “isolate the component of the optical property signal corresponding to a heartbeat to detect a muscle movement” as claimed.
Claim 40. Connor further teaches that the spectrophotometric sensor set comprises
a light emitter and an optical detector ([0489]: FIG.4, at least three optical sensor sets, including sets 403 and 404…each optical sensor set further comprises at least one light emitter 403 or at least one light receiver 404).
Claim 41. Connor further teaches that the light emitter comprises
one or more of: a photodiode and an LED ([0107]: one or more light emitters can be selected from the group consisting of: white LED, blue LED, red LED, infrared LED, and green LED).
Claim 42. Connor further teaches that
the optical detector comprises a photodetector ([0108]: an polygonal array of four optical modules (e.g. sets) of…four light receivers).
Claim 43. Connor further teaches
a plurality of spectrophotometric sensor sets secured by the support ([0109]: a device which is configured to be worn around a body member (e.g. finger, wrist, and/or arm), wherein…at least two optical sensor sets which are held in proximity to the body member by the device; and [0354]: a biometric parameter can be embodied in a sleeve or cuff of a shirt (or other upper body garment)).
Claim 44. Connor further teaches
a signal conditioner comprising one or more of: a lens, a diffuser, a filter, and a lens array ([0145]: an optical (e.g. spectroscopic) sensor can further comprise an optical filter).
Claim 45. Connor further teaches that
the support comprises a garment ([0354]: a device with light emitters and light receivers for measuring a biometric parameter can be embodied in a sleeve or cuff of a shirt (or other upper body garment)).
Claim 46. Connor further teaches that
the support comprises a strap, band, patch, or belt ([0232]: a device with light emitters and light receivers…can be embodied in a smart watch (e.g. the watch housing, the watch strap, or both the housing and the strap)).
Claim 47. Connor further teaches that
the support is configured to fit on one or more of: a user's forearm, wrist, or hand ([0109]: a device which is configured to be worn around a body member (e.g. finger, wrist, and/or arm), wherein…at least two optical sensor sets which are held in proximity to the body member by the device).
Claim 50. Curra further teaches that
the processor is configured to correlate the spectrophotometric sensor with one or more of a muscle or body part movement (Abstract: near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo. In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (i.e., “fingerprints”) of upper limb flexors and extensors; and p.11. In Vivo spectra acquisition: Vis-IR reflectance spectra acquired form the ventral and dorsal aspects of the art were collected using the ASD FiledSpec® 4 Standard-Res field portable spectroradiometer).
Claim 51. Connor further teaches that
the processor comprises processing circuitry ([0480]: a biometric wearable device can further comprise…data processor) – a processor comprises complex integrated circuitry.
Claim 52. Connor further teaches that
the processor comprises a remote processor (([0480]: a biometric wearable device can further comprise…data processor (local, remote, or both local and remote)).
Claims 38 and 81-82 are rejected under 35 U.S.C. 103 as being unpatentable over Connor et al., US 2025/0134381 A1, hereinafter Connor, in view of Currà et al., “Near-infrared spectroscopy as a tool for in vivo analysis of human muscles” Scientific Reports. 2019, 9:8623, hereinafter Currà, further in view of Tscharner et al., “ Removal of the electrocardiogram signal from surface EMG recordings using non-linearly scaled wavelets”. Journal of Electromyography and Kinesiology. 21 (2011) 683-688, hereinafter Tscharner, further in view of Keller et al., US 2017/0102775 A1, hereinafter Keller.
Claim 38. Connor, Curra and Tscharner combined teaches all the limitations of claim 37.
Neither of Connor, Curra and Tscharner teaches the claimed feature associated with the registration.
However, in an analogous body movement tracking field of endeavor, Keller teaches
to adjust the registration of the spectrophotometric representation by comparing the spectrophotometric representation of the region of the subject's skin to a previous spectrophotometric representation of the region of the subject's skin to form an adjusted spectrophotometric representation of the region of the subject's skin ([0042]: the sensor module 142 may include one or more optical elements for providing light from the illumination source to the imaging device; [0051]: The position estimation module PEM340 identifies common features within each image and identifies differences between the common features in the different images to estimate displacement of the features from image to image. Various data analysis methods (e.g., image correlation of image registration) may be used to compare differences between successive images to calculate displacement. Base on identified differences between common features in difference images, the PEM 340 calculates displacement of various features and translates the displacement into positions in a VR environment).
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system or device of Connor, Curra and Tscharner combined employ such features associated “to adjust the registration of the spectrophotometric representation by comparing the spectrophotometric representation of the region of the subject's skin to a previous spectrophotometric representation of the region of the subject's skin to form an adjusted spectrophotometric representation of the region of the subject's skin” as taught in Keller for the advantage of use the registration and alignment for calibration for reducing accumulated error between an estimated position and the initial position, as suggested in Keller, [0051].
Claim 81. Connor teaches in FIGS.1-4 a system for determining a position and/or movement of a body region, the system comprising:
a spectrophotometric sensor set comprising an array of spectrophotometric sensors wherein each spectrophotometric sensor is configured to detect an optical property signal from a tissue, wherein the detected optical property signals correspond to a spectrophotometric representation ([0454]: the biometric wearable device (e.g., finger ring or smart watch) can comprise: a wearable device worn around a body member (e.g., finger, wrist, and/or arm); one or more sensors on the device selected from the group consisting of motion sensor, muscle function monitor, near-infrared spectroscopic (e.g., optical) sensor…., optical sensor; [0437]: heart rate sensor…, PPG sensor…an arcuate array of light emitters around the wearable device, wherein a selected subset of the light emitters are activated to emit light at a given time based on data from the one or more sensors; and one or more light receivers which receive light beams from the light emitters after the light beams have been transmitted through or reflected by the body member; and [0439]: a circumferential array of light emitters around the wearable device, wherein light emitters in the array of light emitters emit light beams with spectral ranges, frequencies, and/or colors which vary over time);
a support configured to hold the spectrophotometric sensor adjacent to a skin surface ([0454]: the biometric wearable device (e.g., finger ring or smart watch) can comprise: a wearable device worn around a body member (e.g., finger, wrist, and/or arm); FIGS.1-4); and
a processor configured to:
receive the spectrophotometric representation from the spectrophotometric sensor set ([0478]: a biometric wearable device…can further comprise a local data processor…a biometric wearable device…can include a data transmitter which transmits data from the light receivers to a remote data processor).
Connor does not teach (1) to detect the position and/or movement of the body region after isolating a component of the optical property signal corresponding to a heartbeat from the received optical property signals, (2) to adjust the registration of the spectrophotometric representation by transforming the spectrophotometric representation based on a comparison between the spectrophotometric representation and a previous spectrophotometric representation to form an adjusted spectrophotometric representation of the region of the subject's skin, and to detect the position and/or movement of the body region based on the adjusted spectrophotometric representation.
In regard to the above feature (1), Connor teaches a muscle function monitor and a near-infrared spectroscopic sensor. However, Connor does not teach that the muscle function monitor is performed by a spectrophotometric sensor set, and the near-infrared spectroscopic sensor is used for detecting muscle movements.
However, in an analogous near IR spectroscopic sensor-based muscle movement detection field of endeavor, Currà teaches such a feature in Abstract: near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo. In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (i.e., “fingerprints”) of upper limb flexors and extensors, which represent specific, accurate, and reproducible measures of the overall biological status of these muscles.
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system of Connor employ such a feature of “detect a muscle movement from the spectrophotometric representation” as taught in Currà for the advantage of “enables more thorough evaluation of the muscular system and optimal monitoring of the effectiveness of therapeutic or rehabilitative interventions”, as suggested in Currà, Abstract.
Neither Connor nor Currà teaches that the muscle movement is detected after isolating a component corresponding to a heartbeat from the received signal.
However, in an analogous muscle movement data processing and analysis field of endeavor, Tscharner teach
the muscle movement is detected after isolating a component corresponding to a heartbeat from the received signal (p.683: Abstract: the EMG signal recorded on some areas of the body, especially from the trunk, is often contaminated with heart muscle electrical activity (ECG) caused by the proximity of the collection sites to the heart. It is therefore necessary to suppress or separate the ECG signal from the EMG signal during the analysis; 1. Introduction, ¶-3: the purpose of this study was to develop a method to remove the ECG from the contaminated EMG signals using the non-linearly scaled wavelets mentioned above and the ICA).
As Connor and Currà combined teaches using optical sensors for measuring the muscle movement and the heartbeat, when Connor, Currà and Tscharner are combined, the isolated component is a component of the optical property signal, and the received signal is a received optical property signal, i.e., “after isolating a component of the optical property signal corresponding to a heartbeat from the received optical property signal” as claimed.
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system of Connor and Currà combined employ such a feature of “detecting the muscle movement after isolating a component corresponding to a heartbeat from the received signal” as taught in Tscharner for the advantage of removing the heartbeat component from a contaminated received signal…resulting cleaned signal retains the spectral properties required for a further time/frequency analysis, as suggested in Tscharner, p.687, last paragraph.
In regard to the above feature (2), neither of Connor, Currà and Tscharner teaches the claimed feature associated with the registration.
However, in an analogous body movement tracking field of endeavor, Keller teaches
to adjust the registration of the spectrophotometric representation by transforming the spectrophotometric representation based on a comparison between the spectrophotometric representation and a previous spectrophotometric representation to form an adjusted spectrophotometric representation of the region of the subject's skin, and to detect the position and/or movement of the body region based on the adjusted spectrophotometric representation ([0042]: the sensor module 142 may include one or more optical elements for providing light from the illumination source to the imaging device; [0051]: The position estimation module PEM340 identifies common features within each image and identifies differences between the common features in the different images to estimate displacement of the features from image to image. Various data analysis methods (e.g., image correlation of image registration) may be used to compare differences between successive images to calculate displacement. Base on identified differences between common features in difference images, the PEM 340 calculates displacement of various features and translates the displacement into positions in a VR environment).
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system or device of Connor, Currà and Tscharner combined employ such features associated “to adjust the registration of the spectrophotometric representation by transforming the spectrophotometric representation based on a comparison between the spectrophotometric representation and a previous spectrophotometric representation to form an adjusted spectrophotometric representation of the region of the subject's skin, and to detect the position and/or movement of the body region based on the adjusted spectrophotometric representation” as taught in Keller for the advantage of use the registration and alignment for calibration for reducing accumulated error between an estimated position and the initial position, as suggested in Keller, [0051].
Claim 82. Keller further teaches that
the anatomical features include skin ridges, blood vessel architecture, tendons, or any combination thereof ([0051]: identifying differences in a series of images captured by the sensor module that captures an illuminated portion of the user’s skin).
Claims 48 and 49 are rejected under 35 U.S.C. 103 as being unpatentable over Connor et al., US 2025/0134381 A1, hereinafter Connor, in view of Currà et al., “Near-infrared spectroscopy as a tool for in vivo analysis of human muscles” Scientific Reports. 2019, 9:8623, hereinafter Currà, further in view of Tscharner et al., “ Removal of the electrocardiogram signal from surface EMG recordings using non-linearly scaled wavelets”. Journal of Electromyography and Kinesiology. 21 (2011) 683-688, hereinafter Tscharner, further in view of Su et al., US 2023/0210402 A1, hereinafter Su.
Claims 48 and 49. Connor, Currà and Tscharner combined teaches all the limitations of claim 37.
Connor further teaches that the processor is configured to wirelessly communicate with another output device ([0349]: a biometric wearable device (e.g. finger ring or smart watch) can include a local data processor. In an example, the device can further comprise a data processor. In an example, a biometric wearable device (e.g. finger ring or smart watch) can further comprise a local data processor which is in wireless electronic communication with a remote data processor. In an example, a biometric wearable device (e.g. finger ring or smart watch) can be part of a system that includes data transmitter which is in electronic communication with a remote data processor. In an example, a device or system can further comprise a cell phone and/or mobile phone; and [0480]: a device or system can further comprise a display screen or touch screen).
In an analogous sensing data information output field of endeavor, Su teaches what is being wirelessly communicated is an indicator of movement in Abstract: the method includes obtaining a movement signal during a motion of a user from at least one sensor,…and displaying the information related to the motion of the user.
As applied to claim 37, Connor, Currà and Tscharner combined teaches sensing a muscle movement. Hence, when Connor, Currà, Tscharner and Su are combined, it teaches that the device output an indication of the muscle movement” in a “wireless” manner, as claimed.
Therefore, it would have been obvious to one of the ordinary skilled in the art before the effective filing date of the claimed invention to have the system or device of Connor, Currà and Tscharner combined employ such features associated “to output an indicator of muscle movement” as taught in Su for the advantage of properly communicate the sensing result to the user, as suggested in Su, [0003].
Conclusion
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/YI-SHAN YANG/Primary Examiner, Art Unit 3798