Abstract
Taking the advantages offered by smart high-performance electronic devices, transradial prosthesis for upper-limb amputees was developed and tested. It is equipped with sensing devices and actuators allowing hand movements; myoelectric signals are detected by Myo armband with 8 ElectroMyoGraphic (EMG) electrodes, a 9-axis Inertial Measurement Unit (IMU) and Bluetooth Low Energy (BLE) module. All data are received through HM-11 BLE transceiver by Arduino board which processes them and drives actuators. Raspberry Pi board controls a touchscreen display, providing user a feedback related to prosthesis functioning and sends EMG and IMU data, gathered via the armband, to cloud platform thus allowing orthopedic during rehabilitation period, to monitor users’ improvements in real time. A GUI software integrating a machine learning algorithm was implemented for recognizing flexion/extension/rest gestures of user fingers. The algorithm performances were tested on 9 male subjects (8 able-bodied and 1 subject affected by upper-limb amelia), demonstrating high accuracy and fast responses.
Highlights
This manuscript describes the realization and testing of a transradial prosthesis addressed to upper-limb amputees managed by a wireless armband able to detect, through electrodes placed on the skin, the myoelectric signals produced by muscle contractions
The myoelectric control of the prosthetic limb was tested through the hardware and software system, which includes the electronic board, described above, for acquiring the EMG signals from Myo armband and GUI software integrating a machine learning algorithm that enables the recognition of flexion/extension/rest gestures of the user’s fingers [20, 21]
The algorithm performances have been tested on 9 male subjects (8 able-bodied and 1 subject affected by congenital upper-limb amelia at the right forearm)
Summary
This manuscript describes the realization and testing of a transradial prosthesis addressed to upper-limb amputees managed by a wireless armband able to detect, through electrodes placed on the skin, the myoelectric signals produced by muscle contractions. The prosthesis can actuate 15 degrees of freedom, three for each finger, with only one motor (instead of five-six motors normally used) and uses two servo-motors for wrist flexion/extension and prono-supination;the torque is automatically distributed among fingers which adapt to the grasped object’s form, so obtaining an optimal grasp [1, 2]. This allows to simplify the control logic and to save on prosthesis cost, weight and dimensions, besides obtaining low power consumption and reduced noise. A Raspberry Pi board manages the display and sends EMG and IMU data via Wi-Fi to a dedicate on-cloud platform to be monitored by orthopedic
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