Characteristics of phantom upper limb mobility encourage phantom-mobility-based prosthesis control. Issue 1 (December 2018)

• Record Type: Journal Article
• Authors: Touillet, Amélie; Peultier-Celli, Laetitia; Nicol, Caroline; Jarrassé, Nathanaël; Loiret, Isabelle; Martinet, Noël; Paysant, Jean; Graaf, Jozina
• Is Part Of: Scientific reports. Volume 8:Issue 1(2018)
• Page Start: 1
• Page End: 10
• Publication Date: 2018-12
• Subjects: Natural history -- Research -- Periodicals; Biology -- Research -- Periodicals; Physical sciences -- Research -- Periodicals; Earth sciences -- Research -- Periodicals; Environmental sciences -- Research -- Periodicals; 502.85
• DOI: 10.1038/s41598-018-33643-0
• Languages: English
• ISSNs: 2045-2322

Abstract

Abstract There is an increasing need to extend the control possibilities of upper limb amputees over their prosthetics, especially given the development of devices with numerous active joints. One way of feeding pattern recognition myoelectric control is to rely on the myoelectric activities of the residual limb associated with phantom limb movements (PLM). This study aimed to describe the types, characteristics, potential influencing factors and trainability of upper limb PLM. Seventy-six below- and above-elbow amputees with major amputation underwent a semi-directed interview about their phantom limb. Amputation level, elapsed time since amputation, chronic pain and use of prostheses of upper limb PLM were extracted from the interviews. Thirteen different PLM were found involving the hand, wrist and elbow. Seventy-six percent of the patients were able to produce at least one type of PLM; most of them could execute several. Amputation level, elapsed time since amputation, chronic pain and use of myoelectric prostheses were not found to influence PLM. Five above-elbow amputees participated in a PLM training program and consequently increased both endurance and speed of their PLM. These results clearly encourage further research on PLM-associated muscle activation patterns for future PLM-based modes of prostheses control.