Ultrasound-Derived Features of Muscle Architecture Provide Unique Temporal Characterization of Volitional Knee Motion

Sonomyography, or dynamic ultrasound imaging of skeletal muscle, has gained significant interest in rehabilitation medicine. Previously, correlations relating sonomyography features of muscle contraction, including muscle thickness, pennation angle, angle between aponeuroses and fascicle length, to muscle force production, strength and joint motion have been established. Additionally, relationships between grayscale image intensity, or echogenicity, with maximum voluntary isometric contraction of muscle have been noted. However, the time relationship between changes in various sonomyography features during volitional motion has yet to be explored, which would highlight if unique information pertaining to muscle contraction and motion can be obtained from this real-time imaging modality. These new insights could inform how we assess muscle function and/or how we use this modality for assistive device control. Thus, our objective was to characterize the time synchronization of changes in five features of rectus femoris contraction extracted from ultrasound images during seated knee extension and flexion. A cross-correlation analysis was performed on data recorded by a handheld ultrasound system as able-bodied subjects completed seated trials of volitional knee extension and flexion. Changes in muscle thickness, angle between aponeuroses, and mean image echogenicity, a change in brightness of the grayscale image, preceded changes in our estimates of pennation angle and fascicle length. The leading nature of these features suggest they could be objective features for early detection of impending joint motion. Finally, multiple sonomyographic features provided unique temporal information associated with this volitional task.Clinical Relevance-This work evaluates the time relationship between five commonly reported features of skeletal muscle architecture during volitional motion, which can be used for targeted clinical assessments and intent detection.