Motorpoint Heatmap of the Hamstring Muscles to Facilitate Neuromuscular Electrical Stimulation
Year: 2024
Type: article
Study design: Observational Study
Abstract: The effectiveness of neuromuscular electrical stimulation (NMES) depends on electrode placement, with placement over the motor points (MPs) being the most effective. This study aimed to determine the MP-distribution and establish a heatmap indicating the probability of finding a MP in different areas of the hamstring (H) muscles. Additionally, inter-individual variations in the number of MPs were investigated. Thirty-one healthy participants (15 females, 16 males), aged 18–65 years, were included. The individual anatomy of the H-muscles, including the biceps femoris (BF), semitendinosus (ST), and semimembranosus (SM), was determined using ultrasound. MPs were located using a MP-search pen. The thigh anatomy was divided into 70 3x3cm areas, and the probability of finding a MP in each area was calculated using the Clopper–Pearson test to create a heatmap. Regression analysis was employed to determine if patient characteristics were associated with the number of MPs. The two best areas, found over BF and ST, exhibited a 39% probability of containing a MP and were significantly more likely to contain a MP compared to 85% of the remaining areas (p < 0.05). Two areas over SM had a 29% probability of containing a MP. BF exhibited a significantly higher number of MPs compared to SM and ST (p < 0.001). Male sex and higher physical activity were independent explanatory factors positively correlated with the number of MPs over BF in the multiple linear regression (R 2 = 0.38, p = 0.001). The MP-heatmap of the H-muscles can effectively facilitate NMES application by highlighting areas with a higher probability of finding a MP. Large inter-individual variations in location and number of MPs were demonstrated.
Source: Annals of Biomedical Engineering
Authors: J. Flodin, P. Amiri, R. Juthberg, P. W. Ackermann
Institutions: Karolinska University Hospital, Karolinska Institutet
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,190
OpenAlex ID: W4404814224