
The aging population in China is increasing the prevalence of degenerative diseases such as knee osteoarthritis (KOA), which significantly impacts the elderly’s quality of life. Traditional Chinese Medicine (TCM) massage has been effective in alleviating KOA symptoms; however, the physician-patient ratio and the physical demands on practitioners pose challenges. This study introduces the KOA massage robot, designed to replicate the seated knee adjustment manipulation, a specific TCM technique. The robot’s structural design and a Particle Swarm Optimization-Back Propagation (PSO-BP) algorithm are integrated to reduce the manipulation required by physicians and to assist in KOA massage treatment. The robot’s force prediction accuracy was determined to be 5.34N on average, and its therapeutic efficacy was supported by Surface Electromyography (sEMG) and Visual Analog Scale (VAS) assessments, demonstrating pain relief and improved quadriceps muscle activation in KOA patients. The experimental validation involved a comparison between traditional manual massage and the robotic intervention. The results showed that the robot could achieve an average increase in integrated EMG (iEMG) of 47%, closely mirroring the 45.37% increase observed in the manual treatment group. Similarly on VAS scores, the robotic intervention group obtained a decrease of 28.12%. This study’s findings not only highlight the potential of integrating TCM principles with modern robotics but also pave the way for a new paradigm in elderly care, where personalized and efficient KOA management is within reach.
Improved particle swarm optimization, Electrical engineering. Electronics. Nuclear engineering, optimization BP neural network, TCM massage, TK1-9971
Improved particle swarm optimization, Electrical engineering. Electronics. Nuclear engineering, optimization BP neural network, TCM massage, TK1-9971
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