Deep learning for biosignal control: Insights from basic to real-time methods with recommendations
Objective. Biosignal control is an interaction modality that allows users to interact with
electronic devices by decoding the biological signals emanating from the movements or …
electronic devices by decoding the biological signals emanating from the movements or …
Long-term upper-extremity prosthetic control using regenerative peripheral nerve interfaces and implanted EMG electrodes
Objective. Extracting signals directly from the motor system poses challenges in obtaining
both high amplitude and sustainable signals for upper-limb neuroprosthetic control. To …
both high amplitude and sustainable signals for upper-limb neuroprosthetic control. To …
Recurrent convolutional neural networks as an approach to position-aware myoelectric prosthesis control
Objective: Persons with normal arm function can perform complex wrist and hand
movements over a wide range of limb positions. However, for those with transradial …
movements over a wide range of limb positions. However, for those with transradial …
Long-term performance of Utah slanted electrode arrays and intramuscular electromyographic leads implanted chronically in human arm nerves and muscles
Objective. We explore the long-term performance and stability of seven percutaneous Utah
Slanted Electrode Arrays (USEAs) and intramuscular recording leads (iEMGs) implanted …
Slanted Electrode Arrays (USEAs) and intramuscular recording leads (iEMGs) implanted …
Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison
Background Advanced prostheses can restore function and improve quality of life for
individuals with amputations. Unfortunately, most commercial control strategies do not fully …
individuals with amputations. Unfortunately, most commercial control strategies do not fully …
Enhancing neuroprosthesis calibration: the advantage of integrating prior training over exclusive use of new data
CJ Thomson, TN Tully, ES Stone… - Journal of Neural …, 2024 - iopscience.iop.org
Objective. Neuroprostheses typically operate under supervised learning, in which a machine-
learning algorithm is trained to correlate neural or myoelectric activity with an individual's …
learning algorithm is trained to correlate neural or myoelectric activity with an individual's …
Portable take-home system enables proportional control and high-resolution data logging with a multi-degree-of-freedom bionic arm
MR Brinton, E Barcikowski, T Davis… - Frontiers in Robotics …, 2020 - frontiersin.org
This paper describes a portable, prosthetic control system and the first at-home use of a
multi-degree-of-freedom, proportionally controlled bionic arm. The system uses a modified …
multi-degree-of-freedom, proportionally controlled bionic arm. The system uses a modified …
Electromyographically controlled prosthetic wrist improves dexterity and reduces compensatory movements without added cognitive load
CD Olsen, NR Olsen, ES Stone, TN Tully… - Scientific Reports, 2024 - nature.com
Wrist function is a top priority for transradial amputees. However, the combined functional,
biomechanical, and cognitive impact of using a powered prosthetic wrist is unclear. Here, we …
biomechanical, and cognitive impact of using a powered prosthetic wrist is unclear. Here, we …
Proportional myoelectric control of a virtual bionic arm in participants with hemiparesis, muscle spasticity, and impaired range of motion
CJ Thomson, FR Mino, DR Lopez, PP Maitre… - Journal of …, 2024 - Springer
Background This research aims to improve the control of assistive devices for individuals
with hemiparesis after stroke by providing intuitive and proportional motor control. Stroke is …
with hemiparesis after stroke by providing intuitive and proportional motor control. Stroke is …
Correcting temporal inaccuracies in labeled training data for electromyographic control algorithms
Electromyographic (EMG) control relies on supervised-learning algorithms that correlate
EMG to motor intent. The quality of the training dataset is critical to the runtime performance …
EMG to motor intent. The quality of the training dataset is critical to the runtime performance …