Elbow Joint Stiffness Functional Scales Based on Hill's Muscle Model and Genetic Optimization.

The ultimate goal of rehabilitation engineering is to provide objective assessment tools for the level of injury and/or the degree of neurorehabilitation recovery based on a combination of different sensing technologies that enable the monitoring of relevant measurable variables, as well as the assessment of non-measurable variables (such as muscle effort/force and joint mechanical stiffness). This paper aims to present a feasibility study for a general assessment methodology for subject-specific non-measurable elbow model parameter prediction and elbow joint stiffness estimation. Ten participants without sensorimotor disorders performed a modified "Reach and retrieve" task of the Wolf Motor Function Test while electromyography (EMG) data of an antagonistic muscle pair (the triceps brachii long head and biceps brachii long head muscle) and elbow angle were simultaneously acquired. A complete list of the Hill's muscle model and passive joint structure model parameters was generated using a genetic algorithm (GA) on the acquired training dataset with a maximum deviation of 6.1% of the full elbow angle range values during the modified task 8 of the Wolf Motor Function Test, and it was also verified using two experimental test scenarios (a task tempo variation scenario and a load variation scenario with a maximum deviation of 8.1%). The recursive least square (RLS) algorithm was used to estimate elbow joint stiffness (Stiffness) based on the estimated joint torque and the estimated elbow angle. Finally, novel Stiffness scales (general patterns) for upper limb functional assessment in the two performed test scenarios were proposed. The stiffness scales showed an exponentially increasing trend with increasing movement tempo, as well as with increasing weights. The obtained general Stiffness patterns from the group of participants without sensorimotor disorders could significantly contribute to the further monitoring of motor recovery in patients with sensorimotor disorders.

Novel multi-pad functional electrical stimulation in stroke patients: A single-blind randomized study.

BACKGROUND: Foot drop is common gait impairment after stroke. Functional electrical stimulation (FES) of the ankle dorsiflexor muscles during the swing phase of gait can help correcting foot drop. OBJECTIVE: To evaluate efficacy of additional novel FES system to conventional therapy in facilitating motor recovery in the lower extremities and improving walking ability after stroke. METHODS: Sixteen stroke patients were randomly allocated to the FES group (FES therapy plus conventional rehabilitation program) (n = 8), and control group (conventional rehabilitation program) n = 8. FES was delivered for 30 min during gait to induce ankle plantar and dorsiflexion. MAIN OUTCOME MEASURES: gait speed using 10 Meter Walk Test (10 MWT), Fugl-Meyer Assessment (FMA), Berg Balance Scale (BBS) and modified Barthel Index (MBI). RESULTS: Results showed a significant increase in gait speed in FES group (p < 0.001), higher than the minimal detected change. The FES group showed improvement in functional independence in the activities of daily living, motor recovery and gait performance. CONCLUSIONS: The findings suggest that novel FES therapy combined with conventional rehabilitation is more effective on walking speed, mobility of the lower extremity, balance disability and activities of daily living compared to a conventional rehabilitation program only.