The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Response to Arguments
On pages 10-11, the applicant argues that the prior art previously applied against the claims fails to teach determination of a muscle fiber velocity and a change in the muscle fiber velocity via a baseline. It is noted that the limitations of the muscle fiber velocity are newly incorporated into the claims. Therefore, the following rejection is made based on these amendments.
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.
Claims 14-19, 21-22, 30-32 and 36 are rejected under 35 U.S.C. 103 as being unpatentable over Zheng (US Patent Pub. No. 2004/0024312) in view of Sikdar et al. (US Patent Pub. No. 2013/0041477), further in view of Sikdar et al. (US Patent Pub. No. 2018/0113205) – herein referred to as Sikdar’205.
Zheng discloses an apparatus comprising a single device (see “compact receiving unit 14 integrated with a transducer” mentioned in paragraph 14 and shown in Figure 2, also see paragraph 71 which teaches that “ultrasound transmitter and receiver 2, digital signal processing module 3, and computer 4 are incorporated into a compact unit that can be worn by a person. Such a compact unit can further include transducers to become an all-in-one unit”) comprising and configured to house:
One or more ultrasound transducers (see paragraph 64, “Referring to FIG. 1, single or multiple ultrasound transducers 1 are attached on the skin surface 8 to transmit ultrasound waves 6 into the soft tissues 9 of a part of the body”);
One or more electrodes (see paragraph 75, which states that “The ultrasound transducer can also be integrated with other types of sensors for monitoring the gesture, posture, and movement of a body part, such as EMG electrodes”, also paragraph 76 discusses combining the system of Zheng with a “body embedded functional electrical stimulation system”, which would obviously include electrodes);
An ultrasound transceiver (see numeral 2 in Figure 1, which is an ultrasound transmitter and receiver - see paragraph 67; it is noted that a “transceiver” as claimed is both a transmitter and a receiver);
One or more processors (see digital signal processing module 3); and
Memory storing processor-executable instruments (it is obvious to one of skill in the art that a processor requires memory storing codes that the processor uses to perform its functions) that, when executed by the one or more processors, cause the apparatus to:
Cause the one or more ultrasound transducers to emit frequency-modulated continuous-wave ultrasound signals, having a signal shape, to a muscle of a subject (see paragraph 65, “The ultrasound signals are continuously recorded and analyzed to detect the changes in the soft tissues, particularly the muscles”, noting that this does not teach frequency-modulation);
Receive, via the ultrasound transceiver, reflected ultrasound signals (see paragraph 64, “reflected and/or scattered ultrasound signals 7 are received”);
…
Analyze the reflected ultrasound signals to provide processed ultrasound signals (see paragraph 64, “reflected and/or scattered ultrasound signals 7 are received, digitized, and processed to obtain various parameters of the signal”); and
Transform one or more of the processed ultrasound signals to a measurement of baseline level of activity of the muscle (see paragraph 72 where the acquisition of reference information is described, which is considered “baseline level of activity of the muscle” for different gestures and postures);
Transform one or more of the processed ultrasound signals to a continuous measurement of dynamic activity associated with the muscle (see Abstract, which teaches that Zheng’s method includes “transmitting an ultrasound signal into the soft tissue, particularly the muscle, of body part and manipulating the reflected ultrasound signal to obtain parameter data. The parameter data is compared to reference information to obtain … movement information for the body part”) … ; and
Calculate, based on the measurement of the baseline level of activity, the continuous measurement of dynamic activity associated with the muscle, …, an indication of a functional condition associated with the muscle (see the Abstract, “The parameter data is compared to reference information to obtain gesture, posture or movement information for the body part”; in other words, the functional condition of the muscle is the “movement information” and/or a change thereof as described in paragraph 65).
However, Zheng does not teach frequency-modulated ultrasound, the use of time-delay spectroscopy for analysis, nor determining muscle fiber velocity and the use of muscle fiber velocity for the indication of a functional condition.
Sikdar teaches an artificial body part control system using ultrasonic imaging (see Title). As shown in Figure 4, the system acquires data at “time 1” when the tissue of interest is at rest, the system collects ultrasonic data via a transducer (see step 402), analyzes the data to produce baseline images (see 406, noting that this is “processed ultrasound signals that are baseline level of activity). Figure 4 then also shows that at “time 2” when the tissue is in contraction, more ultrasound image data is acquired via the transducer (see step 414) and then image data 416 is fed into the analyzer 404, along with the baseline image data 410 where the image data from “time 2” is compared with the baseline image data. Additionally, paragraph 14 teaches that the tissue that undergoes contraction is muscle tissues for which contractions are being monitored. “The control system may determine tissue movement by comparing pixel intensity changes, Doppler shift or phase changes of the received ultrasound signals within a region of interest over time. Comparing such changes within a region of interest allows the control system to determine the nature of any intended tissue movements” (see paragraph 13, last few sentences). Additionally, Sikdar teaches that the analyzer may use vector tissue Doppler imaging to estimate tissue contraction velocities (see paragraph 29). As described in paragraph 30, the tissue movements (e.g., the muscle contraction velocities and other findings described by Sikdar) can be used by the analyzer to decode intended movements for use with the artificial body part.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to determine muscle contraction velocities, as taught by Sikdar, within the system and methods of Zheng for the same purposes proposed by Sikdar (i.e., control of artificial body parts), since Zheng teaches that “This is particularly useful for people with artificial limbs. The transducers or the compact unit can be embedded into the body during or after the amputation surgery. The method and apparatus can be used to obtain information to mechanically manipulate/move artificial limbs in response to gestures and postures of the remained body parts” (see paragraph 76).
However, neither Zheng nor Sikdar teaches the use of frequency-modulation or time-delay spectroscopy for analysis purposes.
Sikdar’205 teaches a low-power ultraportable ultrasound imaging device and associated method (see Title). It is taught that “the methods, systems, and apparatuses disclosed can use time delay spectrometry for low-power, portable, ultrasound imaging” (see paragraph 33). Paragraph 56 teaches that the transmit signal used with this analysis method should be a frequency swept signal (i.e., frequency-modulated; also see the Abstract which states that “A frequency swept signal can be transmitted through a medium, such as human tissue”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to utilize time delay spectrometry analysis, which requires frequency-modulation of the transmitted signal, as taught by Sikar’205, with the system and methods of Zheng as combined with Sikdar, because if and when the system and methods of Zheng with Sikdar are utilized for the purpose of monitoring muscle contraction to control an artificial limb (as described in the combination and both references), this will require a system and techniques that allow for low power and portable systems, which is exactly the type of system and processing techniques disclosed by Sikdar’205 for use with imaging of human tissue. As such, one of ordinary skill in the art would find this useful in creating a low-power ultraportable ultrasound imaging system (see Title of Sikdar’205).
Regarding claim 15, Sikdar teaches that “Embodiments may relate the degree (amount) of tissue contraction to the height of the waveform 802. Embodiments may relate the duration of tissue contraction with the width at 1/2 height of the waveform 800. Embodiments may relate the rate of tissue contraction with the slope 804, taken between 20% and 80% of wave height” (see paragraph 28 and Figure 8). These attributes of the muscle contraction are an indication of the ability of the muscle to generate force.
Regarding claim 16, Zheng teaches that “The body embedded transducer or compact unit can also be used with body embedded functional electrical stimulation system for controlling or monitoring the gesture, posture, or movement of a body part. For the controlling purpose, the ultrasound transducer will be arranged on the muscle that is used to control the electrical stimulation. For the monitoring purpose, the transducer will be arranged on the muscle to be stimulated” (see paragraph 76, emphasis added).
Regarding claim 17, Zheng teaches that “The body embedded transducer or compact unit can also be used with body embedded functional electrical stimulation system for controlling or monitoring the gesture, posture, or movement of a body part. For the controlling purpose, the ultrasound transducer will be arranged on the muscle that is used to control the electrical stimulation. For the monitoring purpose, the transducer will be arranged on the muscle to be stimulated” (see paragraph 76, emphasis added). Also, paragraph 71 states that “real-time information can be used for the prosthesis control, control and monitoring for functional electrical stimulation, computer control, robotic control, and capturing gesture language.”
Regarding claim 18, Sikdar teaches that “Embodiments may relate the degree (amount) of tissue contraction to the height of the waveform 802. Embodiments may relate the duration of tissue contraction with the width at 1/2 height of the waveform 800” (see paragraph 28 and Figure 8). This teaches determining “an amplitude” and “a timing”, which is “one or more” of the Markush grouping. It is noted that this fails to teach the “one or more of” “a frequency”, “a metric output of a machine learning model” and “a duration associated with the one ore more electrical stimulation signals.” However, the claim only requires “one or more”, and this teaches two.
Regarding claim 19, the rejection of claim 14, and specifically the teachings of Sikdar, teaches the use of Doppler imaging (see paragraphs 13 and 29). Also, Sikdar’205 teaches that “time delayed spectrometry (TDS) can provide both Doppler and ranging information” (see paragraph 51).
Regarding claim 21, Zheng teaches throughout the disclosure that the device should be small to cause less discomfort to the user (see paragraph 6), that the unit should be “compact” (see paragraph 71) and can be the size of a wrist-watch (see paragraph 71). It is estimated that numeral 14 in Figure 2 of Zheng appears to be substantially on the scale of 100 mm, but Zheng does not explicitly disclose the dimensions of the device. Zheng discloses the claimed invention except for the exact dimensions of the apparatus (see paragraph 71 which teaches the transducers/transceivers, processor and computer on a single compact unit, while Sikdar teaches a battery pack 33 in paragraph 17, and Sikdar’205 teaches battery power 302 in Figure 3 and paragraph 53); i.e., that the ultrasound transceiver, the one or more processors, and the memory collectively comprise a length dimension and a width dimension of less than or equal to 50 millimeters. It would have been an obvious matter of design choice to modify the apparatus to be less than or equal to 50 millimeters in length and width since such a modification would have involved a mere change in the size of a component. A change in size is generally recognized as being within the level of ordinary skill in the art. In re Rose, 105 USPQ 237 (CCPA 1955).
Regarding claim 22, it is noted that claim 14 has explicitly been rejected based on a determination of muscle velocity.
Regarding claims 30-31, it is noted that Sikdar’205 illustrates both TDS (i.e., for claim 31) and pulse echo (i.e., for claim 30) setups (see paragraph 17 and Figures 10, 12-13).
Regarding claim 32, it is re-iterated that Sikdar’205 teaches a swept frequency-modulation imaging (see unit 101 in Figure 1, or unit 201 in Figure 2, as well as step 610 in Figure 6).
Regarding claim 36, it is noted that Sikdar’205 illustrates both TDS (i.e., for claim 31) (see paragraph 17 and Figures 10, 12-13).
Claims 23-26, 28-29, 34-35 and 37 are rejected under 35 U.S.C. 103 as being unpatentable over Zheng in view of Sikdar and Sikdar’205, and further in view of Liu et al. (CN 110420383 A).
Regarding claim 23, it is noted that most of claim 23 is identical to claim 14 and therefore, the rejection of claim 14 is incorporated herein by reference in its entirety, which is based on Zheng, Sikdar and Sikdar’205. However, claim 23 adds “stimulate, based on one or more electrical stimulation signals, the muscle, wherein the one or more electrical stimulation signals are associated with a first one or more parameters” (see lines 18-20) and the “stimulate” recitations of the last four (4) lines of the claim.
With regard to “stimulate, based on one or more electrical stimulation signals, the muscle, wherein the one or more electrical stimulation signals are associated with a first one or more parameters” (see lines 18-20 of claim 23), it is noted that Zheng teaches that “The body embedded transducer or compact unit can also be used with body embedded functional electrical stimulation system for controlling or monitoring the gesture, posture, or movement of a body part. For the controlling purpose, the ultrasound transducer will be arranged on the muscle that is used to control the electrical stimulation. For the monitoring purpose, the transducer will be arranged on the muscle to be stimulated” (see paragraph 76, emphasis added). Also, paragraph 71 states that “real-time information can be used for the prosthesis control, control and monitoring for functional electrical stimulation, computer control, robotic control, and capturing gesture language” (emphasis added). In other words, Zheng positively teaches the use of its system with electrical stimulation, and therefore this teaches stimulation of the muscle based on electrical stimulation signals. Additionally, it is inherent that “electrical stimulation signals are associated with… parameters”, since there has to be current applied which will include frequency, amplitude, etc. Therefore, the teachings of Zheng also teach lines 18-20 of claim 23.
With regard to “stimulate, based on another one of more electrical stimulation signals, the muscle, wherein the another one or more electrical stimulation signals are associated with one or more of the second one or more parameters, including the muscle fiber velocity”, it is noted that although Zheng teaches both monitoring and control of an electrical stimulation system via its ultrasound imaging methods, there is not a clear description of utilizing feedback from the monitoring to improve the electrical stimulation, as in this recitation of claim 23. However, Liu teaches “an adjustable functional electrical stimulation control method based on multi-mode fusion feedback” (see Abstract). Further, Liu teaches, on the seventh (7th) page of the accompanying machine translation, that “In this embodiment, the electrical stimulation output current waveform adjusting method, except the upper computer control mode, further can be automatically adjusted by means of feedback to initiate ensures the stability of electric stimulation effect in application of the muscle contraction to assist movement in functional electrical stimulation. As shown in FIG. 4, first collecting the sensing information of the … myoelectric/ultrasonic … or myoelectric/ultrasonic /FSR by high-density electrode, after transmitting to the upper computer by using software to analyze the movement intention configured aiming at the output position and parameter of the stimulation current and high-density electrode output. after electrical stimulation induced muscle contraction motion, the collected sensing information continuously effect and composed of an upper computer analyzing and evaluating electrical stimulation movement caused by the actual effect and the desired effect of regulating the position and parameters of the electrical stimulation output current to keep the electrical stimulation inducing stable effect of muscle contraction motion.” Therefore, Liu teaches a closed loop feedback system between sensed data, which includes ultrasonic imaging/measurements, for optimizing electrical stimulation for desired muscle contraction.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to utilize a closed loop feedback system between ultrasonic sensing and electrical stimulation, as taught by Liu, within the system and methods of Zheng as combined with Sikdar and Sikdar’205, in order “to ensure stable efficacy of electrical stimulation”, thereby reducing muscle fatigue (see #4 on page 5 of the machine translation of Liu).
Regarding claim 24, it is noted that the delivery of electrical stimulation will obviously have a desired outcome, and when providing electrical stimulation explicitly for purposes of muscle contractions, there would obviously be a “target twitch amplitude”. In other words, there would be a desire for some resulting amount of contraction if the desire is to cause a contraction.
Regarding claim 25, it is noted that claim 23 requires “one or more second one or more parameters”, including a second muscle fiber velocity”, and the rejection includes Sikdar for this purpose. Therefore, this reads on “a velocity” in claim 25.
Regarding claim 26, it is noted that Zheng teaches that “The parameter data is compared to reference information to obtain gesture, posture or movement information for the body part” (see Abstract; in other words, the functional condition of the muscle is the “movement information” and/or a change thereof as described in paragraph 65). Also, Figure 4 of Sikdar illustrates baseline images acquired at “time 1” and tissue contraction images at “time 2”, which are both compared for analytical purposes within analyzer 404.
Regarding claim 28, the rejection of claim 14, and specifically the teachings of Sikdar, teaches the use of Doppler imaging (see paragraphs 13 and 29). Also, Sikdar’205 teaches that “time delayed spectrometry (TDS) can provide both Doppler and ranging information” (see paragraph 51).
Regarding claim 29, it is noted that claim 23 requires “one or more second one or more parameters”, including a second muscle fiber velocity”, and the rejection includes Sikdar for this purpose. Therefore, this reads on “a velocity” in claim 29.
Regarding claim 34, it is noted that the combination described above in the rejection of claim 23 teaches electrodes used for providing electrical stimulation to the muscle which would be monitored by the ultrasound, as described in Zheng.
Regarding claim 35, Figure 2 of Zheng illustrates placement of a unitary device on the leg, which is placed over the muscles it would be evaluating and stimulating.
Regarding claim 37, it is noted that Sikdar’205 illustrates both TDS (i.e., for claim 31) (see paragraph 17 and Figures 10, 12-13).
Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Zheng in view of Sikdar, Sikdar’205 and Liu as applied to claim 26 above, and further in view of Buhlmann et al. (US Patent Pub. No. 2005/0283204).
Zheng in combination with Sikdar, Sikdar’205 and Liu is described above with respect to claim 26. However, none of these references explicitly teach that muscle fatigue (or recovery) is analyzed.
Buhlmann teaches automated adaptive muscle stimulation methods (see Title). In paragraph 81, Buhlmann teaches that “The measurement of a degree of muscular fatigue is an indication to a user of an electro-stimulation device that there will be little or no benefit obtained from continuing muscle stimulation during a particular treatment session. In one embodiment, the detection of muscle fatigue is based upon a measurement of a shift in fusion frequency. As depicted in FIG. 10, fusion occurs when the individual mechanical responses (graph B) to the electrical excitation pulses (graph A) can no longer be differentiated in the muscle (graph C). It is known that the fusion frequency decreases when fatigue increases due to a longer relaxation time in the individual mechanical responses, shown as the dotted curve in graph B.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to utilize the determination of muscle fatigue, as taught by Buhlmann, within the system and methods of the combination of Zheng with Sikdar, Sikdar’205 and Liu, because if enacting an automatic, closed-loop feedback system as taught by the combination, one would not want to continue to apply electrical stimulation to the patient if no benefit is achieved due to muscle fatigue, and knowing that this can be detected when there is no differentiation in the muscle upon electrical stimulation means the ultrasound monitoring, upon detecting no change, can therefore detect the fatigue (and subsequently the recovery thereof when changes are detected, if so tested).
Claim 33 is rejected under 35 U.S.C. 103 as being unpatentable over Zheng in view of Sikdar and Sikdar’205 as applied to claim 14 above, and further in view of Kidwell et al. (US Patent Pub. No. 2017/0256699), and further in view of Khuri-Yakub et al. (US Patent Pub. No. 2004/0085858).
Zheng in combination with Sikdar and Sikdar’205 is described above with respect to claim 14. However, while Zheng teaches that the ultrasound transducer is flexible (see paragraph 44), it does not teach a piezoelectric co-polymer and polyamide substrate with conductive micro-patterns.
Kidwell teaches an ultrasound transceiver (piezoelectric micromechanical ultrasonic transducer (PMUT) that is composed of a flexible (see Abstract and Figure 1A) piezoelectric co-polymer (see paragraph 65 which states that the PMUT comprises a piezoelectric layer and a polymer layer) with conductive micro-patterns (see paragraph 65 again, which states that patterns are created on a first and second electrode; these are considered to be “micro-patterns” because of the scale of the transceiver (i.e., because it is a “micromechanical…transducer”)). It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to utilize a co-polymer with conducive micro-patterns, as taught by Kidwell, within the system and methods for the purpose of creating the transducer because the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results (KSR, 550 U.S. at 416, 82 USPQ2d at 1395).
However, these references do not explicitly teach a polyamide substrate.
Khuri-Yakub teaches that using a polyamide substrate as a support member when fabricating PMUTs is known in the art (see paragraph 5). It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to use a polyamide substrate for creating a PMUT for the system of Zheng and the proposed combination, as this is explicitly taught by Khuri-Yakub as a common substrate choice in ultrasonic transducers, and because the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results (KSR, 550 U.S. at 416, 82 USPQ2d at 1395).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JAMES KISH/ Primary Examiner, Art Unit 3792
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