摘要
Neurorehabilitation involves training of brain activity, which influences the resistive torque and electromyogram. This quantitative evaluation is numerical modeling of biomaterial of human body. Measurement for rehabilitation and developing numerical modeling in patients are useful for information technology education with healthcare background. The resistive torque and electromyogram were measured. Electromyogram is the neuronal activity from eight lower limb muscles. Both activities are output signals for angle input signals. The resistive torque of a stroke patient shows a hysteresis curve, and this is a velocity-dependent component, particular for stroke. Differentiated angle by muscle spindle, a velocity-dependent component, is a stretch reflex （spasticity）. In an electromyogram of a stroke patient, SLR （stretch reflex via spinal cord） means a short latency reflex, and LLR （stretch reflex via cerebral cortex） means a long latency reflex. An example of some stroke electromyogram shows long latency reflex, and this is voluntary movement during the experiment. The example of some stroke resistive torque reveals that viscoelasticity is used for the intrinsic component. The example of some stroke electromyogram reveals that long latency reflex is used for the reflex component of lower limbs. Current research needs improvement. Intrinsic viscoelasticity is modeled by a second-order differential equation. The reflex component of stroke patients is modeled by a double exponential function. Open source software is in use. Information technology-based analyses by numerical modeling would be applied in future healthcare education.
