{"id":"AIBD-0604","title":"Randomized crossover home trial at Shirley Ryan AbilityLab: pattern-recognition prosthesis control outperforms direct control for eight transhumeral amputees with TMR","summary":"In a randomized crossover home trial, eight people with above-elbow amputation and nerve transfer surgery did better on two hand-function tests with pattern-recognition control; seven preferred it.","date_observed":"2017-10-23","date_basis":"source publication","date_precision":"day","benefit_status":"reported","source_collection":null,"source_entry":null,"account":"Levi Hargrove, Laura Miller, Kristi Turner and Todd Kuiken of the Center for Bionic Medicine at the Shirley Ryan AbilityLab in Chicago ran a randomized crossover trial (NCT03097978) with eight people who had an amputation above the elbow and targeted muscle reinnervation (TMR), a surgery that moves arm nerves onto remaining muscles. Each person used a custom prosthesis built from commercial parts at home for at least six weeks with direct control and for the same time with pattern recognition control, which uses machine learning algorithms to learn patterns in the muscle signals. A random order decided which method came first. With pattern recognition, participants scored better on the Southampton Hand Assessment Procedure (p = 0.04) and moved three clothespins in 90.2 seconds on average against 137 seconds with direct control (p = 0.02). The Box and Blocks Test and the ACMC showed no significant differences. Seven of the eight participants preferred pattern recognition. In a 2021 review, F. Mereu and colleagues at Università Campus Bio-Medico di Roma and the INAIL Prosthetic Center, who declare no conflicts of interest, report the same results. Scientific Reports published the trial on 23 October 2017. The sample is small, participants noted some unintended movements, and Hargrove and Kuiken have a financial interest in Coapt, which sells pattern recognition systems, although the study used no Coapt products.","category":"general benefit","unexpected":false,"purpose":"Pattern recognition control was built to let amputees operate several prosthetic joints in sequence without switching modes. The better function and the preference that the trial measured were that purpose.","system":"Myoelectric pattern recognition control (machine-learning classification of residual-limb EMG) on a custom transhumeral prosthesis built from commercially available parts","model_version":null,"developer":"Center for Bionic Medicine, Shirley Ryan AbilityLab (formerly the Rehabilitation Institute of Chicago), with Northwestern University","deployer":"Center for Bionic Medicine, Shirley Ryan AbilityLab, with home use by trial participants","location":"Chicago, Illinois, United States (laboratory testing) and participants' homes","domain":"Healthcare","segment":null,"benefit_type":"Improved Accessibility","taxonomy_note":null,"registry_ids":{},"ratings":[{"group":"personal","depth":2,"reason":"Participants moved three clothespins in 90.2 seconds with pattern recognition against 137 seconds with direct control, and seven of eight preferred it."}],"ai_role":{"status":"assessed","statement":"A randomized crossover design compares the same prosthesis under machine-learning pattern recognition control and under conventional direct control."},"evidence":[{"kind":"peer-reviewed study","citation":"Mereu F, Leone F, Gentile C, Cordella F, Gruppioni E, Zollo L. 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