New method enhances muscle activity identification for treatment

Researchers at Carnegie Mellon University have made a significant breakthrough in understanding muscle activity. They have developed a new method that uses high-density surface electromyography (HD-sEMG) sensors to analyze muscle activity in crowded areas, such as the forearm. The technique combines HD-sEMG with other advanced methods, including peripheral nerve stimulation and ultrasound imaging. This allows for better accuracy in identifying muscle actions. The research is published in the Journal of Neurophysiology. With this method, scientists can electrically stimulate specific nerves to activate muscles. The HD-sEMG setup used in the study features a 64-channel grid placed on the skin to capture electrical signals produced by muscle contractions. These signals help researchers understand when and how muscles are working. One of the key advantages of this research is the ability to reduce electrical interference from nearby muscles, known as crosstalk. The researchers found that their filters could almost eliminate crosstalk from distances of 2.55 cm or more, leading to clearer results. This helps in mapping muscle activity more accurately. The findings are important for diagnosing and treating conditions related to strokes, spinal cord injuries, and other neurological disorders. The improved methods could also enhance rehabilitation therapies and the control of prosthetic limbs. Currently, the team is applying this method to clinical patients, such as stroke victims and amputees experiencing phantom limb pain. The goal is to analyze muscle activity patterns in these individuals, aiming to create tailored treatment plans for better recovery.