Prosecution Insights
Last updated: May 29, 2026
Application No. 16/293,767

Grasp Assistance System and Method

Final Rejection §102§103
Filed
Mar 06, 2019
Priority
Mar 09, 2018 — provisional 62/640,609
Examiner
HOBAN, MELISSA A
Art Unit
3774
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Myomo Inc.
OA Round
11 (Final)
63%
Grant Probability
Moderate
12-13
OA Rounds
0m
Est. Remaining
76%
With Interview

Examiner Intelligence

Grants 63% of resolved cases
63%
Career Allowance Rate
390 granted / 619 resolved
-7.0% vs TC avg
Moderate +13% lift
Without
With
+12.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 10m
Avg Prosecution
24 currently pending
Career history
668
Total Applications
across all art units

Statute-Specific Performance

§101
0.1%
-39.9% vs TC avg
§103
79.2%
+39.2% vs TC avg
§102
7.8%
-32.2% vs TC avg
§112
3.2%
-36.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 619 resolved cases

Office Action

§102 §103
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/10/2025 has been entered. The previous objection to the claims is withdrawn in light of applicant’s amendments. Claims 1-6, 11-12, 14-17, 22, 23, 26, and 27 are currently pending in this application. Response to Arguments Applicant's arguments filed 10/10/2025 have been fully considered but they are not persuasive. With regard to applicant’s argument that Sallum does not teach or suggest operating a powered orthotic device to perform a grasping movement task as a chain of motion primitives being implemented as a recorded complex series of movements, the examiner disagrees. Sallum clearly teaches that the system can learn a motion profile by providing little or no resistance to the thumb while it is moved by the clinician or users through a range of motion, and that the device can record the motion profile including joint positions, motions, and velocities which can be saved into memory for later use (paragraph 0046). The movement or motion is recorded by the control unit by recording the distance and direction a pivot joint is moved or by recording a first position of the pivot joint and a second position of the pivot joint, such that the recording can include a list of one or more movement directions over a distance or time period or a series of positional points (e.g., angles) sensed by the sensors (paragraph 0011). The list and/or series disclosed by Sallum is construed to be a chain of motion primitives, as claimed by application. Further, Sallum teaches that the isolated orthosis for thumb actuation can be used as an assistive device in which the recorded motion profiles can be repeated for use during every day activities, each of which include a complex series of movements (paragraphs 0036 and 0076). The examiner therefore maintains that the motion profile of Sallum is a grasping movement task as a chain of motion primitives, with the chain of motion primitives being implemented as a recorded complex series of movements (i.e., putting toothpaste on a toothbrush, feeding oneself, pulling on pants, taking money out of a wallet, etc.), as claimed by applicant. With regard to applicant’s argument that Sallum does not teach that the activities noted in Sallum are implemented as a chain of motion primitives that combines in parallel a plurality of the primitives, the examiner disagrees. Sallum shows, for example in fig. 4A, the CMC joint 146 is in abduction and the MCP joint 148 is in flexion at the same time the hand is positioned in an open form ready for grasping. Therefore, the motion primitives (joint positions) are combined in parallel to be implemented as a chain of motion primitives. Claim Rejections - 35 USC § 102 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 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) 1, 3, 6, 11, 12, 14, 17, 22, 23, 26, and 27 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US patent Application Publication No. 2015/0148728 A1 to Sallum et al. (Sallum). Regarding at least claim 1 Sallum teaches an orthosis system that includes an orthotic device adapted to be worn on the hand of a subject that includes at least one brace component coupled to one or more fingers of the hand and including at least one joint permitting movement of one or more fingers, as well as one or more actuators and a control unit that can be operated to facilitate everyday tasks or for treatment of therapy (abstract). Sallum meets the limitations of a computer-implemented method employing at least one hardware implemented computer processor for controlling a grasp control system to assist a wearer with a grasping movement task (paragraphs 0036-0037 disclose a grasp control system to assist a wearer with a grasping movement task), the method comprising: operating the at least one hardware implemented computer processor (paragraph 0076 discloses a small computer or microprocessor that includes a processor) to execute program instructions for: monitoring a movement intention signal of a grasping movement muscle of the wearer (paragraph 0069 discloses sensors that are provided on the brace portion to monitor and report to the controller); identifying a volitional operator input for the grasping movement task from the movement intention signal (paragraph 0069 discloses that the sensors can include electromyography, accelerometers, gyroscopes, magnetometers, strain sensors, optical sensors, optical encoders, hall-effect sensors, bend sensors, load cells, piezoresistive sensors, or any combination thereof); responsive to the movement intention signal, operating a powered orthotic device to perform the grasping movement task as a chain of motion primitives (paragraph 0077 discloses that the appropriate control signals are determined and then sent back to the control unit to be used to control the actuators to perform the grasping movement task as of a chain of motion primitives), wherein: each motion primitive is a fundamental unit of grasping motion defined along a movement path with a single degree of freedom (paragraph 0011 discloses that the movement or motion is recorded by the control unit by recording the distance and direction a pivot joint is moved or by recording a first position of the pivot joint and a second position of the pivot joint, such that the recording can include a list of one or more movement directions over a distance or time period or a series of positional points (e.g., angles) sensed by the sensors – each recorded position of the joint is construed to be a motion primitive which may be a fundamental unit of grasping motion defined along a movement path with a single degree of freedom as claimed, depending on the activity the user intends to record for later use); the chain of motion primitives is implemented as a recorded complex series of movements, performed dynamically by the user for accomplishing the grasping movement task, the recorded complex series of movements having been configured for on-demand activation by the wearer (paragraph 0046 discloses that during operating mode, the system can learn a motion profile by recording the motion profile during the passive motion, which is performed dynamically by the wearer, and saving/recording the motion profile into memory for later use, then loading and executing the save motion profile when necessary, i.e. on-demand; paragraph 0076 further specifies that the motion profile can be later repeated by the device to design new assistive motions for the subject; the assistive motions disclosed by Sallum are a chain of motion primitives implemented as a recorded complex series of movements, for example putting toothpaste on a toothbrush, brushing teeth, feeding oneself, putting on clothing, taking money out of wallet, etc., as disclosed in paragraph 0036); the powered orthotic device includes a grasp actuator (paragraph 0056 discloses a controller provided to control the actuators that manipulate the brace causing one or more digits to move, which can include a button, a switch, a joystick, a dial or a knob and is construed to be a grasp actuator), a thumb actuator, and finger actuators (paragraph 0056 discloses actuators 170 that are adapted to engage and actuate one or more fingers of the hand, including the thumb and fingers as disclosed in paragraphs 0065 and 0066, and paragraph 0068 discloses additional actuators provided for separate motor controls), the grasp actuator containing a grasp control processor (controller is disclosed to include a processor as disclosed in paragraph 0076), the grasp actuator being configured to generate powered signals to cause the thumb actuator and the finger actuators to assist with grasping, holding, and releasing an object (paragraph 0076 discloses the control unit connected to a power source to control the actuators and move the brace portion, for example to execute the assistive motions disclosed in paragraph 0036 which require grasping, holding, and releasing an object), and the chain of motion primitives combines in parallel a plurality of the primitives thereof (i) to create a grasping motion with at least two degrees of freedom (the motion profiles disclosed in paragraph 0036 include grasping motion with at least two degrees of freedom), and (ii) to shape the grasping motion by performance at a variable speed controlled by the volitional operator input (paragraph 0076 discloses that the joint speed for each joint can be set at any time during operation and is therefore construed to shape the motion by performance at a variable speed controlled by the operator based on information used to identify the VOI, as disclosed in paragraph 0045). Regarding at least claim 3 Sallum teaches the method of claim 1. Sallum also teaches wherein the grasping movement muscle is a first grasping movement muscle, and the method further comprises comprising: monitoring a second movement intention signal of a second grasping movement muscle of the wearer, wherein the volitional operator input is identified from both movement intention signals (paragraph 0043 discloses surface electromyography sensors such that attempts by the subject move the muscles in the hand can be used to drive the actuators – the movement of multiple muscles with EMG sensors meets the limitations of monitoring first and second movement intention signals of a first and second grasping movement muscle, respectively, to identify the volitional operator input which determines operation of the orthotic device). Regarding at least claim 6 Sallum teaches the method of claim 1, further comprising: monitoring a finger force signal generated by one or more fingers of the wearer related to the grasping movement task, wherein the volitional operator input is identified from the movement intention signal and the finger force signal (paragraph 0090 discloses additional sensors connected to the control unit, which detect forces and/or torques, so that the control unit can operate on the signals and computer the appropriate actuation signal). Regarding at least claim 11 Sallum teaches the method of claim 1, wherein the movement intention signal is an electromyography (EMG) signal (paragraph 0042 discloses that the sensors can include electromyography, for monitoring a movement intention signal that is an EMG signal). Regarding at least claim 12 Sallum meets the limitations of a computer-implemented grasp control system for assisting a wearer with a grasping movement task (paragraphs 0036-0037 disclose a grasp control system to assist a wearer with a grasping movement task that is computer-implemented as disclosed in paragraph 0076), the system comprising: a muscle movement sensor configured for monitoring a grasping movement muscle of the wearer to produce a movement intention signal (paragraph 0043 discloses surface electromyography sensors such that attempts by the subject move the muscles in the hand can be used to drive the actuators through the production of an EMG signal/movement intention signal); a powered orthotic device (110) configured for assisting grasping motion of the wearer (paragraph 0087 discloses assistance in a grasping motion of the wearer), the powered orthotic device including a grasp actuator, a thumb actuator, and finger actuators, the grasp actuator containing at least one grasp control processor, wherein the grasp actuator is configured to generate powered signals to cause the thumb actuator and finger actuators to assist with grasping, holding, and releasing an object (paragraph 0056 discloses a controller provided to control the actuators that manipulate the brace causing one or more digits to move, which can include a button, a switch, a joystick, a dial or a knob and is construed to be a grasp actuator), a thumb actuator, and finger actuators (paragraph 0056 discloses actuators 170 that are adapted to engage and actuate one or more fingers of the hand, including the thumb and fingers as disclosed in paragraphs 0065 and 0066, and paragraph 0068 discloses additional actuators provided for separate motor controls), the grasp actuator containing a grasp control processor (controller is disclosed to include a processor as disclosed in paragraph 0076), the grasp actuator being configured to generate powered signals to cause the thumb actuator and the finger actuators to assist with grasping, holding, and releasing an object (paragraph 0076 discloses the control unit connected to a power source to control the actuators and move the brace portion, for example to execute the assistive motions disclosed in paragraph 0036 which require grasping, holding, and releasing an object); data storage memory configured for storing grasp control software (paragraph 0076 discloses a processor and associated memory and one or more programs that interact with hardware interfaces to control the actuators and move the brace portion of the orthotic), the movement intention signal (paragraph 0076 also discloses that the memory stores recorded motion profiles associated with the EMG signals/movement intention signals), and system information, the system information including: (a) system settings related to operation of the grasp control system and the powered orthotic device, the system settings including user specific settings selected from the group consisting of signal gains, signal thresholds, operation speeds, grasp preferences and combinations thereof (paragraph 0076 discloses setting the range of motion and joint speed for each joint), and (b) device history information, (c) shared performance information (paragraph 0076 discloses recording the joint position and speed of motion during operation so that the motion profile, i.e. shared performance information, can later be reviewed and analyzed by a clinical professional), (d) historical control settings, or (e) machine learning data; the at least one grasp control processor including at least one hardware processor coupled to the data storage memory and configured to execute the grasp control software (paragraph 0076 discloses a processor that includes a hardware processor coupled to the memory for executing the control software as claimed), wherein the grasp control software includes processor readable instructions to implement a grasp control algorithm (paragraph 0077 discloses execution of the grasp control algorithm) for: identifying a volitional operator input for the grasping movement task from the movement intention signal (paragraph 0069 discloses that the sensors can include electromyography, accelerometers, gyroscopes, magnetometers, strain sensors, optical sensors, optical encoders, hall-effect sensors, bend sensors, load cells, piezoresistive sensors, or any combination thereof); responsive to the movement intention signal, operating the powered orthotic device, to perform the grasping movement task as a chain of motion primitives (paragraph 0077 discloses that the appropriate control signals are determined and then sent back to the control unit to be used to control the actuators to perform the grasping movement task as of a chain of motion primitives), each motion primitive being a fundamental unit of grasping motion defined along a movement path with a single degree of freedom (paragraph 0011 discloses that the movement or motion is recorded by the control unit by recording the distance and direction a pivot joint is moved or by recording a first position of the pivot joint and a second position of the pivot joint, such that the recording can include a list of one or more movement directions over a distance or time period or a series of positional points (e.g., angles) sensed by the sensors – each recorded position of the joint is construed to be a motion primitive which may be a fundamental unit of grasping motion defined along a movement path with a single degree of freedom as claimed, depending on the activity the user intends to record for later use), the chain of motion primitives being implemented as a recorded complex series of movements, performed dynamically by the wearer for accomplishing the grasping movement task, the recorded complex series having been configured for on-demand activation by the wearer (paragraph 0046 discloses that during operating mode, the system can learn a motion profile by recording the motion profile during the passive motion, which is performed dynamically by the user, and saving/recording the motion profile into memory for later use, then loading and executing the save motion profile when necessary, i.e. on-demand; paragraph 0076 further specifies that the motion profile can be later repeated by the device to design new assistive motions for the subject; the assistive motions disclosed by Sallum are a chain of motion primitives implemented as a recorded complex series of movements, for example putting toothpaste on a toothbrush, brushing teeth, feeding oneself, putting on clothing, taking money out of wallet, etc., as disclosed in paragraph 0036), and the chain of motion primitives combines in parallel a plurality of the primitives thereof (i) to create a grasping motion with at least two degrees of freedom (the motion profiles disclosed in paragraph 0036 include grasping motion with at least two degrees of freedom), and (ii) to shape the grasping motion by performance at a variable speed controlled by the volitional operator input (paragraph 0076 discloses that the joint speed for each joint can be set at any time during operation and is therefore construed to shape the motion by performance at a variable speed controlled by the operator based on information used to identify the VOI, as disclosed in paragraph 0045). Regarding at least claim 14 Sallum teaches the grasp control system of claim 12, wherein the grasping movement muscle is a first grasping movement muscle, and the grasp control system further comprises comprising: a second muscle movement sensor configured for monitoring a second grasping movement muscle of the wearer to produce a second movement intention signal, wherein the grasp control algorithm identifies the volitional operator input from both movement intention signals (paragraph 0043 discloses surface electromyography sensors such that attempts by the subject move the muscles in the hand can be used to drive the actuators – the movement of multiple muscles with EMG sensors meets the limitations of monitoring first and second movement intention signals of a first and second grasping movement muscle, respectively, to identify the volitional operator input which determines operation of the orthotic device). Regarding at least claim 17 Sallum teaches the grasp control system of claim 12, further comprising: a finger force sensor configured for monitoring a finger force signal generated by one or more fingers of the wearer related to the grasping movement task, wherein the grasp control algorithm identifies the volitional operator input from the movement intention signal and the finger force signal (paragraph 0090 discloses additional sensors connected to the control unit, which detect forces and/or torques, so that the control unit can operate on the signals and computer the appropriate actuation signal). Regarding at least claim 22 Sallum teaches the grasp control system of claim 12, wherein the muscle movement sensor is an electromyography (EMG) signal sensor (paragraph 0042 discloses that the sensors can include electromyography, for monitoring a movement intention signal that is an EMG signal). Regarding at least claim 23 Sallum teaches the method of claim 1, wherein operating the at least one hardware processor to execute program instructions further includes operating the at least one hardware processor to execute program instructions for providing a user interface by which the wearer is able to select a grasp movement task from a menu of grasp movement tasks (paragraph 0077 discloses interface elements that the wearer operates to perform at least one everyday activity as disclosed in claim 13). Regarding at least claim 26 Sallum teaches the method of claim 1, wherein the recorded complex series of movements is configured to perform an arm-hand procedure by the power orthotic device (each of the motion profiles, including, for example, putting toothpaste on a toothbrush, are pre-recorded as a complex series of movements, and then performed by the power orthotic of Sallum in an arm-hand procedure). Regarding at least claim 27 Sallum teaches the grasp control system of claim 12, wherein the recorded complex series of movements is configured to perform an arm-hand procedure by the power orthotic device (each of the motion profiles, including, for example, putting toothpaste on a toothbrush, are pre-recorded as a complex series of movements, and then performed by the power orthotic of Sallum in an arm-hand procedure). 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) 4, 5, 15, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sallum, as applied to claims 1, 3, 12, and 14 above, in view of US Patent Application Publication No. 2013/0253705 A1 to Goldfarb et al. (Goldfarb). Regarding at least claims 4 and 15 Sallum teaches the method and grasp control system of claims 3 and 14, respectively, including monitoring the grasping movement muscles by positioning sensors appropriately to send signals to actuators of an orthotic device to assist with everyday activities. However, Sallum does not explicitly teach wherein the grasping movement muscles are antagonistic muscles. Goldfarb teaches a control system for a myoelectric grasping device that includes monitoring of EMG sensors from different muscle groups, preferably an antagonist muscle pair, to drive the device with bi-directional EMG input (abstract and paragraph 0021), for the purpose of transitioning the device into different poses such a first EMG signal drives the device along a first motion axis and a different EMG signal would be used, in a reverse order, to return the device along the reverse path, to its original configuration (paragraph 0021). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Sallum to include bi-directional EMG input by monitoring grasping movement muscles that are antagonistic muscles, in order to transition the device along a forward path by activating a grasping movement muscle and along a reverse path by activating an opposite muscle, as taught by Goldfarb. Regarding at least claims 5 and 16 Sallum teaches the method and grasp control system of claims 1 and 12, respectively, including that the grasping movement tasks can include feeding oneself, for example (paragraph 0036). The examiner notes that performance of the chain of motion primitives in a reverse order would be necessary when multiple bites are taken. However, Sallum does not explicitly teach wherein performing the grasping movement task further comprises: undoing a portion of the grasping movement task based on the volitional operator input by performing a portion of the chain of motion primitives in reverse order. Goldfarb teaches a control system for a myoelectric grasping device that includes monitoring of EMG sensors from different muscle groups, preferably an antagonist muscle pair, to drive the device with bi-directional EMG input (abstract and paragraph 0021), for the purpose of transitioning the device into different poses such a first EMG signal drives the device along a first motion axis and a different EMG signal would be used, in a reverse order, to return the device along the reverse path, to its original configuration (paragraph 0021). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Sallum to specify that performing the grasping movement task further comprises: undoing a portion of the grasping movement task based on the volitional operator input by performing a portion of the chain of motion primitives in reverse order, in order to return the device to its original configuration, as taught by Goldfarb, for example when another bite is needed during feeding, as implicitly taught by Sallum. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MELISSA A HOBAN whose telephone number is (571)270-5785. The examiner can normally be reached Monday-Friday 8:00AM-5:00PM. 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, Melanie Tyson can be reached at 571-272-9062. 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. /M.A.H/Examiner, Art Unit 3774 /MELANIE R TYSON/Supervisory Patent Examiner, Art Unit 3774
Read full office action

Prosecution Timeline

Show 42 earlier events
Sep 10, 2025
Response after Non-Final Action
Oct 10, 2025
Request for Continued Examination
Oct 16, 2025
Response after Non-Final Action
Nov 06, 2025
Non-Final Rejection mailed — §102, §103
Feb 06, 2026
Response Filed
Feb 17, 2026
Interview Requested
Feb 25, 2026
Examiner Interview Summary
May 27, 2026
Final Rejection mailed — §102, §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12594165
EXPANDABLE MEDICAL IMPLANT FOR ADOLESCENT CRANIUM DEFECTS
4y 10m to grant Granted Apr 07, 2026
Patent 12569348
BEARING COMPONENT FOR ARTIFICIAL KNEE JOINT
4y 2m to grant Granted Mar 10, 2026
Patent 12564496
HYBRID FIXATION FEATURES FOR THREE-DIMENSIONAL POROUS STRUCTURES FOR BONE INGROWTH AND METHODS FOR PRODUCING
4y 0m to grant Granted Mar 03, 2026
Patent 12533239
CONICAL PATELLA RESURFACING
7y 3m to grant Granted Jan 27, 2026
Patent 12533237
CONNECTING SLEEVE FOR ANCHORING SHAFTS OF TWO OPPOSITELY ARRANGED PROSTHESES
3y 8m to grant Granted Jan 27, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

12-13
Expected OA Rounds
63%
Grant Probability
76%
With Interview (+12.9%)
3y 10m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 619 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month