A Novel Design of a Robotic Glove System for Patients With Brachial Plexus Injuries

Abstract

This paper presents the design of an exoskeleton glove system for people who suffer from the brachial plexus injuries in an effort to restore their lost grasping functionality. The robotic system consists of an embedded controller and a portable glove system. The glove system consists of Linear Series Elastic Actuators (SEA), Rotary SEA and optimized finger linkages to provide motion to each finger and a coupled motion of the hand and the wrist. The design is based on various functionality requirements such as being lightweight and portable for activities of daily living, especially for grasping. The contact force at each fingertip and bending angle of each finger are measured for future implementation of intelligent control algorithms for autonomous grasping. To provide better flexibility and comfort for the users, abduction and adduction of each finger as well as flexion of the thumb were taken into consideration in the design. The glove system is adjustable for different hand sizes. The micro-controllers and batteries are integrated on the forearm in order to provide a completely portable design solution.

Data Driven Calibration and Control of Compact Lightweight Series Elastic Actuators for Robotic Exoskeleton Gloves

“…D) A general purpose robotic hand exoskeleton with series elastic actuation [12]. E) A robotic glove system for patients with brachial plexus injuries [13].…”

“…Xu, et al proposed a low-cost, compact, lightweight SEA used in the RML exoskeleton [13]. This design is shown in sub-figure E of Fig.…”

“…This paper uses the SEA design presented in Xu, et al's paper [13] as an example. This SEA is compact, lightweight, low-cost, and provides sufficient force output(Maxium 20N on fingertips).…”

“…FORCE CONTROL When controlling the SEA, traditional force feedback control will not work well due to the low control frequency. In a compact design mentioned in Xu, et al's [13] paper, the onboard micro-controllers run ten threads and control seven different SEAs, which means it does not have the computational power to run the prediction network. Cloud computing is required for prediction networks, but the delay in cloud computing restricts the control speed.…”

Personalized voice activated grasping system for a robotic exoskeleton glove

“…The latest generation RML exoskeleton glove is based on a rigid linkage mechanism connected with a linear SEA on each finger, to control each of the linkage mechanisms [17]. A rotatory SEA is used to control the MCP joint of the thumb [18], and a linear SEA to control the wrist joint.…”