The PrHand: Functional Assessment of an Underactuated Soft-Robotic Prosthetic Hand

Abstract

Functional tests aim to compare the functionality of a prosthesis with a human hand. The main objective of this work is to present and evaluate an affordable prosthesis (PrHand) built with soft robotic technologies and novel joints based on compliant mechanisms. Two functional tests have been selected in this work. The first is the AHAP protocol, which evaluates how the prosthesis performs eight different grips; three variables are considered: grasping, maintaining, and grasping ability score (GAS). The results were 69.03% with 57.77% in grasping and 80.28% in maintaining. The second test is the AM-ULA, which evaluates the prosthesis by performing 23 Activities of Daily Living. PrHand prosthesis had a score of 2.5 over 4.0. The functionality of the PrHand prosthesis has similar results to other prostheses evaluated in the literature. The comparison with the human hand was 69%. PrHand presents a promising solution for amputees in developing countries regarding cost and functionality.

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses

“…Moreover, we depict the error bars corresponding to the standard deviation for each angle value. As the characterization was performed over the prosthetic fingers, it was difficult to ensure that each opening/closing cycle was performed in the same way, generating errors in the angles and in the voltage, which is expected due to the nature of soft robotic prostheses construction [ 44 ]. It is observed that with increments, the error in the angles proportionally increases the error in the measured voltages.…”

“…In particular, this protocol allows the comparison of different robotic hands by grasping different objects. This protocol was already implemented with the PrHand prosthesis in [ 44 ]. The assessment performed eight types of grasp with three objects per grip type.…”

“…This sensor methodology monitors the physical interaction during grasping activities to detect the object type grasped by a data-driven approach. The haptic sensor system developed here was implemented in the upper-limb soft robotics prosthesis PrHand (described in [ 44 ]). The soft-sensor system resembles the kinesthetic perception of the human hand by implementing two sensing modalities, finger joint angles and fingertip contact force measurements implemented in the prosthetic fingers.…”

Pressure and Angle Sensors with Optical Fiber for Instrumentation of the PrHand Hand Prosthesis

“…In [17], the prosthesis functionally was assessed for which grip types the prosthesis better performs, comparing to the grasp types the human hand performs during activities of daily life, namely: hook, spherical grip, tripod pinch, and spherical grip. In [19] the angle sensors information was used for grasp types recognition with machine learning (ML) algorithms, taking into account the grasp types aforementioned.…”

“…The PrHand is an upper-limb prosthesis based on soft robotics and complaint mechanisms, described in [17]. The computer-aided design (CAD) and the actual prototype are presented in Figure 1.…”