Simultaneous Control of 2DOF Upper-Limb Prosthesis With Body Compensations-Based Control: A Multiple Cases Study

Abstract

Controlling several joints simultaneously is a common feature of natural arm movements. Robotic prostheses shall offer this possibility to their wearer. Yet, existing approaches to control a robotic upper-limb prosthesis from myoelectric interfaces do not satisfactorily respond to this need: standard methods provide sequential jointby-joint motion control only; advanced pattern recognitionbased approaches allow the control of a limited subset of synchronized multi-joint movements and remain complex to set up. In this paper, we exploit a control method of an upper-limb prosthesis based on body motion measurement called Compensations Cancellation Control (CCC). It offers a straightforward simultaneous control of the intermediate joints, namely the wrist and the elbow. Four transhumeral amputated participants performed the Refined Rolyan Clothespin Test with an experimental prosthesis alternatively running CCC and conventional joint-by-joint myoelectric control. Task performance, joint motions, body compensations and cognitive load were assessed. This experiment shows that CCC restores simultaneity between prosthetic joints while maintaining the level of performance of conventional myoelectric control (used on a daily basis by three participants), without increasing compensatory motions nor cognitive load.

Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces

“…When the convex-relaxation techniques are not applicable for some objective/cost, the greedy heuristic algorithms such as sequential forward selection (SFS) were proposed to find a feasible solution to the problem (10) with constraints (11). Although such algorithm is applicable to our problem formulation, given the existence of composite features we doubt the solution by the heuristics is very likely to be suboptimal.…”

“…1) Objective Function Relaxation: The non-convex objective function in (10) is cast into a convex one. To do so, the class label y is turned into continuous variables using the dummy variables and scoring matrix [23].…”

“…Let matrix B be defined as B = 1 n Y T Y. Instead of solving the non-convex objective (10), we can solve the following problem with a convex objective…”

“…The algorithm adds one sensor with all available features at a time based on some performance metric (usually classification accuracy) until q sensors are selected [11], [13]. A similar approach can be applied to our problem formulation (10,11), when l is set sufficiently large. However, the results can be suboptimal [30].…”

“…I N recent years, there has been great interest in developing Human-Prosthetic Interfaces (HPIs) that enable coordinated movement with the user's limb and body in order to produce human-like natural movements for people wearing upper limb prostheses [1]- [10]. This differs from the more traditional approach in powered prostheses, where the movement of each degree of freedom is explicitly controlled by the human user through the signal from one/a pair of sensors (e.g.…”