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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. 

Over the past few decades, there have been many studies of human-human physical interaction to better understand why humans physically interact so effectively and how dyads outperform individuals in certain motor tasks. Because of the different methodologies and experimental setups in these studies, however, it is difficult to draw general conclusions as to the reasons for this improved performance. In this study, we propose an open-source experimental framework for the systematic study of the effect of human-human interaction, as mediated by robots, at the ankle joint. We also propose a new framework to study various interactive behaviors (i.e., collaborative, cooperative, and competitive tasks) that can be emulated using a virtual spring connecting human pairs. To validate the proposed experimental framework, we perform a transparency analysis, which is closely related to haptic rendering performance. We compare muscle EMG and ankle motion data while subjects are barefoot, attached to the unpowered robot, and attached to the powered robot implementing transparency control. We also validate the performance in rendering a virtual springs covering a range of stiffness values (5-50 Nm/rad) while the subjects track several desired trajectories(sine waves at frequencies between 0.1 and 1.1 Hz). Finally, we study the performance of the system in human-human interaction under nine different interactive conditions. Finally, we demonstrate the feasibility of the system in studying human-human interaction under different interactive behaviors. 

An ultra-low-power gesture and gait classification SoC is presented for rehabilitation application featuring (1) mixed-signal feature extraction and integrated low-noise amplifier eliminating expensive ADC and digital feature extraction, (2) an integrated distributed deep neural network (DNN) ASIC supporting a scalable multi-chip neural network for sensor fusion with distortion resiliency for low-cost front end modules, (3) onchip learning of DNN engine allowing in-situ training of user specific operations. A 12-channel 65nm CMOS test chip was fabricated with 1μW power per channel, less than 3ms computation latency, on-chip training for user-specific DNN model and multi-chip networking capability. 

Challenges associated with current prosthetic technologies limit the quality of life of lower-limb amputees. Passive prostheses lead amputees to walk slower, use more energy, fall more often, and modify their gait patterns to compensate for the prosthesis’ lack of net-positive mechanical energy. Robotic prostheses can provide mechanical energy, but may also introduce challenges through controller design. Fortunately, talented researchers are studying how to best control robotic leg prostheses, but the time and resources required to develop prosthetic hardware has limited their potential impact. Even after research is completed, comparison of results is confounded by the use of different, researcher-specific hardware. To address these issues, we have developed the Open-source Leg (OSL): a scalable robotic knee/ankle prosthesis intended to foster investigations of control strategies. This paper introduces the design goals, transmission selection, hardware implementation, and initial control benchmarks for the OSL. The OSL provides a common hardware platform for comparison of control strategies, lowers the barrier to entry for prosthesis research, and enables testing within the lab, community, and at home. 

Challenges associated with current prosthetic technologies limit the quality of life of lower-limb amputees. Passive prostheses lead amputees to walk slower, use more energy, fall more often, and modify their gait patterns to compensate for the prosthesis' lack of net-positive mechanical energy. Robotic prostheses can provide mechanical energy, but may also introduce challenges through controller design. Fortunately, talented researchers are studying how to best control robotic leg prostheses, but the time and resources required to develop prosthetic hardware has limited their potential impact. Even after research is completed, comparison of results is confounded by the use of different, researcher-specific hardware. To address these issues, we have developed the Open-source Leg (OSL): a scalable robotic knee/ankle prosthesis intended to foster investigations of control strategies. This paper introduces the design goals, transmission selection, hardware implementation, and initial control benchmarks for the OSL. The OSL provides a common hardware platform for comparison of control strategies, lowers the barrier to entry for prosthesis research, and enables testing within the lab, community, and at home.