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1. First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study

   https://doi.org/10.3389/fbioe.2022.876836  

   Engdahl, Susannah M.; Acuña, Samuel A.; King, Erica L.; Bashatah, Ahmed; Sikdar, Siddhartha (May 2022, Frontiers in Bioengineering and Biotechnology)

   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. 

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2. Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks

   https://doi.org/10.3390/s22239350  

   Murray, Rosemarie; Mendez, Joel; Gabert, Lukas; Fey, Nicholas P.; Liu, Honghai; Lenzi, Tommaso (December 2022, Sensors)

   Many people struggle with mobility impairments due to lower limb amputations. To participate in society, they need to be able to walk on a wide variety of terrains, such as stairs, ramps, and level ground. Current lower limb powered prostheses require different control strategies for varying ambulation modes, and use data from mechanical sensors within the prosthesis to determine which ambulation mode the user is in. However, it can be challenging to distinguish between ambulation modes. Efforts have been made to improve classification accuracy by adding electromyography information, but this requires a large number of sensors, has a low signal-to-noise ratio, and cannot distinguish between superficial and deep muscle activations. An alternative sensing modality, A-mode ultrasound, can detect and distinguish between changes in superficial and deep muscles. It has also shown promising results in upper limb gesture classification. Despite these advantages, A-mode ultrasound has yet to be employed for lower limb activity classification. Here we show that A- mode ultrasound can classify ambulation mode with comparable, and in some cases, superior accuracy to mechanical sensing. In this study, seven transfemoral amputee subjects walked on an ambulation circuit while wearing A-mode ultrasound transducers, IMU sensors, and their passive prosthesis. The circuit consisted of sitting, standing, level-ground walking, ramp ascent, ramp descent, stair ascent, and stair descent, and a spatial–temporal convolutional network was trained to continuously classify these seven activities. Offline continuous classification with A-mode ultrasound alone was able to achieve an accuracy of 91.8±3.4%, compared with 93.8±3.0%, when using kinematic data alone. Combined kinematic and ultrasound produced 95.8±2.3% accuracy. This suggests that A-mode ultrasound provides additional useful information about the user’s gait beyond what is provided by mechanical sensors, and that it may be able to improve ambulation mode classification. By incorporating these sensors into powered prostheses, users may enjoy higher reliability for their prostheses, and more seamless transitions between ambulation modes. 

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3. A multiarticulate pediatric prosthetic hand for clinical and research applications

   https://doi.org/10.3389/frobt.2022.1000159  

   Battraw, Marcus A.; Young, Peyton R.; Joiner, Wilsaan M.; Schofield, Jonathon S. (October 2022, Frontiers in Robotics and AI)

   Although beginning to emerge, multiarticulate upper limb prostheses for children remain sparse despite the continued advancement of mechatronic technologies that have benefited adults with upper limb amputations. Upper limb prosthesis research is primarily focused on adults, even though rates of pediatric prosthetic abandonment far surpass those seen in adults. The implicit goal of a prosthesis is to provide effective functionality while promoting healthy social interaction. Yet most current pediatric devices offer a single degree of freedom open/close grasping function, a stark departure from the multiple grasp configurations provided in advanced adult devices. Although comparable child-sized devices are on the clinical horizon, understanding how to effectively translate these technologies to the pediatric population is vital. This includes exploring grasping movements that may provide the most functional benefits and techniques to control the newly available dexterity. Currently, no dexterous pediatric research platforms exist that offer open access to hardware and programming to facilitate the investigation and provision of multi-grasp function. Our objective was to deliver a child-sized multi-grasp prosthesis that may serve as a robust research platform. In anticipation of an open-source release, we performed a comprehensive set of benchtop and functional tests with common household objects to quantify the performance of our device. This work discusses and evaluates our pediatric-sized multiarticulate prosthetic hand that provides 6 degrees of actuation, weighs 177 g and was designed specifically for ease of implementation in a research or clinical-research setting. Through the benchtop and validated functional tests, the pediatric hand produced grasping forces ranging from 0.424–7.216 N and was found to be comparable to the functional capabilities of similar adult devices. As mechatronic technologies advance and multiarticulate prostheses continue to evolve, translating many of these emerging technologies may help provide children with more useful and functional prosthesis options. Effective translation will inevitably require a solid scientific foundation to inform how best to prescribe advanced prosthetic devices and control systems for children. This work begins addressing these current gaps by providing a much-needed research platform with supporting data to facilitate its use in laboratory and clinical research settings. 

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4. Under pressure: design and validation of a pressure-sensitive insole for ankle plantar flexion biofeedback during neuromuscular gait training

   https://doi.org/10.1186/s12984-022-01119-y  

   Conner, Benjamin C.; Fang, Ying; Lerner, Zachary F. (December 2022, Journal of NeuroEngineering and Rehabilitation)

   Abstract BackgroundElectromyography (EMG)-based audiovisual biofeedback systems, developed and tested in research settings to train neuromuscular control in patient populations such as cerebral palsy (CP), have inherent implementation obstacles that may limit their translation to clinical practice. The purpose of this study was to design and validate an alternative, plantar pressure-based biofeedback system for improving ankle plantar flexor recruitment during walking in individuals with CP. MethodsEight individuals with CP (11–18 years old) were recruited to test both an EMG-based and a plantar pressure-based biofeedback system while walking. Ankle plantar flexor muscle recruitment, co-contraction at the ankle, and lower limb kinematics were compared between the two systems and relative to baseline walking. ResultsRelative to baseline walking, both biofeedback systems yielded significant increases in mean soleus (43–58%, p < 0.05), and mean (68–70%, p < 0.05) and peak (71–82%, p < 0.05) medial gastrocnemius activation, with no differences between the two systems and strong relationships for all primary outcome variables (R = 0.89–0.94). Ankle co-contraction significantly increased relative to baseline only with the EMG-based system (52%, p = 0.03). ConclusionThese findings support future research on functional training with this simple, low-cost biofeedback modality. 

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5. Integrating Upper-Limb Prostheses with the Human Body: Technology Advances, Readiness, and Roles in Human–Prosthesis Interaction

   https://doi.org/10.1146/annurev-bioeng-110222-095816  

   Huang, He Helen; Hargrove, Levi J; Ortiz-Catalan, Max; Sensinger, Jonathon W (July 2024, Annual Review of Biomedical Engineering)

   Significant advances in bionic prosthetics have occurred in the past two decades. The field's rapid expansion has yielded many exciting technologies that can enhance the physical, functional, and cognitive integration of a prosthetic limb with a human. We review advances in the engineering of prosthetic devices and their interfaces with the human nervous system, as well as various surgical techniques for altering human neuromusculoskeletal systems for seamless human–prosthesis integration. We discuss significant advancements in research and clinical translation, focusing on upper limbprosthetics since they heavily rely on user intent for daily operation, although many discussed technologies have been extended to lower limb prostheses as well. In addition, our review emphasizes the roles of advanced prosthetics technologies in complex interactions with humans and the technology readiness levels (TRLs) of individual research advances. Finally, we discuss current gaps and controversies in the field and point out future research directions, guided by TRLs. 

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