Ultrasound-based sensing of muscle deformation, known as sonomyography, has shown promise for accurately classifying the intended hand grasps of individuals with upper limb loss in offline settings. Building upon this previous work, we present the first demonstration of real-time prosthetic hand control using sonomyography to perform functional tasks. An individual with congenital bilateral limb absence was fitted with sockets containing a low-profile ultrasound transducer placed over forearm muscle tissue in the residual limbs. A classifier was trained using linear discriminant analysis to recognize ultrasound images of muscle contractions for three discrete hand configurations (rest, tripod grasp, index finger point) under a variety of arm positions designed to cover the reachable workspace. A prosthetic hand mounted to the socket was then controlled using this classifier. Using this real-time sonomyographic control, the participant was able to complete three functional tasks that required selecting different hand grasps in order to grasp and move one-inch wooden blocks over a broad range of arm positions. Additionally, these tests were successfully repeated without retraining the classifier across 3 hours of prosthesis use and following simulated donning and doffing of the socket. This study supports the feasibility of using sonomyography to control upper limb prostheses in real-world applications.

IntroductionPatellar tendon adaptations occur in response to mechanical load. Appropriate loading is necessary to elicit positive adaptations with increased risk of injury and decreased performance likely if loading exceeds the capacity of the tendon. The aim of the current study was to examine intra-individual associations between workloads and patellar tendon properties and neuromuscular performance in collegiate volleyball athletes.MethodsNational Collegiate Athletics Association Division I men's volleyball athletes (n = 16, age: 20.33 ± 1.15 years, height: 193.50 ± 6.50 cm, body mass: 84.32 ± 7.99 kg, bodyfat%: 13.18 ± 4.72%) competing across 9 weeks of in-season competition participated. Daily measurements of external workloads (i.e., jump count) and internal workloads [i.e., session rating of perceived exertion (sRPE)] were recorded. Weekly measurements included neuromuscular performance assessments (i.e., countermovement jump, drop jump), and ultrasound images of the patellar tendon to evaluate structural adaptations. Repeated measures correlations (r-rm) assessed intra-individual associations among performance and patellar tendon metrics.ResultsWorkload measures exhibited significant negative small to moderate (r-rm =−0.26–0.31) associations with neuromuscular performance, negative (r-rm = −0.21–0.30), and positive (r-rm = 0.20–0.32) small to moderate associations with patellar tendon properties.DiscussionMonitoring change in tendon composition and performance adaptations alongside workloads may inform evidence-based frameworks toward managing and reducing the risk of the development of patellar tendinopathy in collegiate men's volleyball athletes.

Ultrasound-based sensing of muscle deformation, known as sonomyography, has shown promise for accurately classifying the intended hand grasps of individuals with upper limb loss in offline settings. Building upon this previous work, we present the first-in-human demonstration of real-time prosthetic hand control using sonomyography to perform functional tasks. An individual with congenital bilateral limb absence was fitted with sockets containing a low-profile ultrasound transducer placed over forearm muscle tissue in the residual limbs. A classifier was trained using linear discriminant analysis to recognize ultrasound images of muscle contractions for three discrete hand configurations (rest, tripod grasp, index finger point) under a variety of arm positions designed to cover the reachable workspace. A prosthetic hand mounted to the socket was then controlled using this classifier. Using this real-time sonomyographic control, the participant was able to complete three functional tasks that required selecting different hand grasps in order to grasp and move one-inch wooden blocks over a broad range of arm positions. Additionally, these tests were successfully repeated without retraining the classifier across three hours of prosthesis use and following simulated donning and doffing of the socket. This study supports the feasibility of using sonomyography to control upper limb prostheses in real-world applications.

Ultrasound-based sensing of muscle deformation, known as sonomyography, has shown promise for accurately classifying the intended hand grasps of individuals with upper limb loss in offline settings. Building upon this previous work, we present the first demonstration of real-time prosthetic hand control using sonomyography to perform functional tasks. An individual with congenital bilateral limb absence was fitted with sockets containing a low-profile ultrasound transducer placed over forearm muscle tissue in the residual limbs. A classifier was trained using linear discriminant analysis to recognize ultrasound images of muscle contractions for three discrete hand configurations (rest, tripod grasp, index finger point) under a variety of arm positions designed to cover the reachable workspace. A prosthetic hand mounted to the socket was then controlled using this classifier. Using this real-time sonomyographic control, the participant was able to complete three functional tasks that required selecting different hand grasps in order to grasp and move one-inch wooden blocks over a broad range of arm positions. Additionally, these tests were successfully repeated without retraining the classifier across three hours of prosthesis use and following simulated donning and doffing of the socket. This study supports the feasibility of using sonomyography to control upper limb prostheses in real-world applications.