0 Item(s)
Prosthetic Free Papers - Upper Limb Prostheses
2021 Annual Meeting Education Content
Keyword(s)
AM2021-FP03, free papers, fp3
Credit Information
2.0 Credits (Scientific)
Author(s)
Riley Knox, MSc; Sheila Pach, CO; Susannah Engdahl, PhD; Todd Farrell, PhD; Matthew Wernke, PhD
Description
Frequency Analysis of Acceleration Patterns During Activities of Daily Living in Upper-Limb Prosthesis User
Riley Knox, MSc
Evidence suggests that upper limb prosthesis users experience a high prevalence of falls and so identifying behavior that could lead to falls may help inform interventions to reduce fall risk. The purpose of this study was to analyze kinematic data obtained during walking and upper limb goal-oriented tasks to perform task classification.
Clinical Evaluation of a Novel Low-Cost Voluntary Closing Prosthetic Hand
Sheila Pach, CO
A low-cost anthropomorphic prosthetic hand has been developed to meet the upper limb prosthetic needs in developing countries. The primary aim of this study was to compare the low-cost hand to a commercially available body powered hand. The secondary aim was to gather clinical feedback in regards to the function and appearance of the low-cost hand.
Sonomyography Enables Robust Hand Gesture Classification with Minimal Training
Susannah Engdahl, PhD
Sonomyography is a novel modality for controlling upper limb prostheses that relies on ultrasound to sense muscle deformation within the residual limb. Although prior work has shown that sonomyography can accurately classify multiple motion classes in individuals with limb loss, it remains unclear whether user training can lead to further improvements in classification performance. In this work, we demonstrate that users are able to achieve high classification rates upon their initial exposure to sonomyography and that training does not improve their performance.
Comparison Of Upper Extremity Myoelectric Interface And Control Methodologies: Preliminary Results From The Halfway Point
Matthew Wernke, PhD
Clean and reliable signals is important for myoelectric control of an upper extremity prosthesis. Here we will provide an update on results from an ongoing study of different interface design and control methodologies.
Improved Multi-Articulating Hand Grasp Selection with Voice Recognition Control
Todd Farrell, PhD
This presentation describes the Voice Activated Prothesis Interface (VAPI), which incorporates the ability for the use of the voice to generate prosthesis control signals to complement the user's electromyographic (EMG) control signals. Data is presented from testing on persons with amputation that showed that users were able to access the desired grip pattern of a multi-articulating hand 1.8 times more frequently with voice control when performing various outcomes measures. Results also show that tasks could be completely 19% more quickly and with less frustration and fatigue when using EMG with voice control versus standard EMG control.