Decline in balance control is an issue for older adults as it leads to an increased risk of falling which may result in serious injury. Mitigating this risk may be achieved through balance training and exercise, but lack of adherence to an exercise program often occurs.

Simultaneous and proportional control (SPC) of neural-machine interfaces uses magnitudes of smoothed electromyograms (EMG) as control inputs. Though surface EMG (sEMG) electrodes are common for clinical neural-machine interfaces, intramuscular EMG (iEMG) electrodes may be indicated in some circumstances (e.g., for controlling many degrees of freedom).

Rodent models are decisive for translational research in healthy and pathological conditions of motor function thanks to specific similarities with humans. Here, we present an upgraded version of the M-Platform, a robotic device previously designed to train mice during forelimb retraction tasks.

A mathematical modeling for description of oscillation suppression by deep brain stimulation (DBS) is explored in this work. High frequency DBS introduced to the basal ganglia network can suppress pathological neural oscillations that occur in the Parkinsonian state.

For stroke survivors and many other people with upper-extremity impairment, daily life can be difficult without properly functioning arms. Some modern physical therapy exercises focus on rehabilitating people with these troubles by correcting patients’ perceptions of their own body to eventually regain complete control and strength over their arms again.

Sensory processing differences, including responses to auditory, visual, and tactile stimuli, are ideal targets for early detection of neurodevelopmental risks, such as autism spectrum disorder. However, most existing studies focus on the audiovisual paradigm and ignore the sense of touch.