Early decoding of walking tasks with minimal set of EMG channels.

Objective.Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decoding performance and minimal set-up burden is yet to be determined. Here we propose an efficient decoding approach obtaining high decoding performance by observing only a fraction of the gait duration with a limited number of recording sites.Approach.Thirteen transfemoral amputee subjects performed five motor tasks while recording EMG signals from four muscles and inertial signals from the prosthesis. A support-vector-machine-based algorithm decoded the gait modality selected by the patient from a finite set. We investigated the trade-off between the robustness of the classifier's accuracy and the minimization of (i) the duration of the observation window, (ii) the number of EMG recording sites, (iii) the computational load of the procedure, measured the complexity of the algorithm.Main results.When including pre-foot-strike data in the decoding, the combination of three EMG recording sites and the inertial signals led to correct rates above 94% at the 20% of the gait cycle, showing the best trade-off between invasiveness of the setup and accuracy of the classifier. The complexity of the algorithm proved to be significantly higher when applying a polynomial kernel compared to a linear one, while the correct rate of the classifier generally showed no differences between the two approaches. The proposed algorithm led to high performance with a minimal EMG set-up and using only a fraction of the gait duration.Significance. These results pave the way for efficient control of powered lower-limb prostheses with minimal set-up burden and a rapid classification output.

Degree of Safety Against Falls Provided by 4 Different Prosthetic Knee Types in People With Transfemoral Amputation: A Retrospective Observational Study.

OBJECTIVE: People with transfemoral amputation have balance and mobility problems and are at high risk of falling. An adequate prosthetic prescription is essential to maximize their functional levels and enhance their quality of life. This study aimed to evaluate the degree of safety against falls offered by different prosthetic knees. METHODS: A retrospective study was conducted using data from a center for prosthetic fitting and rehabilitation. Eligible individuals were adults with unilateral transfemoral amputation or knee disarticulation. The prosthetic knee models were grouped into 4 categories: locked knees, articulating mechanical knees (AMKs), fluid-controlled knees (FK), and microprocessor-controlled knees (MPK). The outcome was the number of falls experienced during inpatient rehabilitation while wearing the prosthesis. Association analyses were performed with mixed-effect Poisson models. Propensity score weighting was used to adjust causal estimates for participant confounding factors. RESULTS: Data on 1486 hospitalizations of 815 individuals were analyzed. Most hospitalizations (77.4%) were related to individuals with amputation due to trauma. After propensity score weighting, the knee category was significantly associated with falls. People with FK had the highest rate of falling (incidence rate = 2.81 falls per 1000 patient days, 95% CI = 1.96 to 4.02). FK significantly increased the risk of falling compared with MPK (incidence rate ratio [IRRFK-MPK] = 2.44, 95% CI = 1.20 to 4.96). No other comparison among knee categories was significant. CONCLUSIONS: Fluid-controlled prosthetic knees expose inpatients with transfemoral amputation to higher incidence of falling than MPK during rehabilitation training. IMPACT: These findings can guide clinicians in the selection of safe prostheses and reduction of falls in people with transfemoral amputation during inpatient rehabilitation.

Targeted Muscle Reinnervation and Osseointegration for Pain Relief and Prosthetic Arm Control in a Woman with Bilateral Proximal Upper Limb Amputation.

BACKGROUND: Bilateral proximal upper limb loss is a dramatic life-changing event. Replacement of the lost function with prosthetic arms, including multiple mechatronic joints, has remained a challenge from the control, comfort, and pain management perspectives. Targeted muscle reinnervation (TMR) is a peripheral nerve surgical procedure proposed to improve the intuitive control of the prosthetic arm and for neuroma and phantom pain management. Moreover, osseointegrated percutaneous implants (OPIs) allow for direct skeletal attachment of the prosthetic arm, ensuring freedom of movement to the patient's residual articulations. CASE DESCRIPTION: We have reported the first combined application of TMR and an OPI to treat a 24-year-old woman with a bilateral amputation at the shoulder level on the right side and at the very proximal transhumeral level on the left side. TMR was performed bilaterally in a single day, accounting for the peculiar patient's anatomy, as preparatory stage to placement of the OPI, and considering the future availability of implantable electromyographic sensors. The 2 OPI surgeries on the left side were completed after 8.5 months, and prosthetic treatment was completed 17 months after TMR. CONCLUSIONS: The use of TMR resolved the phantom pain bilaterally and the right-side neuroma pain. It had also substantially reduced the left side neuroma pain. The actual prosthetic control result was intuitive, although partially different from expectations. At 2 years after TMR, the patient reported improvement in essential activities of daily living, with a remarkable preference for the OPI prosthesis. Only 1 suspected case of superficial infection was noted, which had resolved. Overall, this combined treatment required a highly competent multidisciplinary team and exceptional commitment by the patient and her family.