A novel approach to automatically quantify the level of coincident activity between EMG and MMG signals.

Although previous studies have highlighted both similarities and differences between the timing of electromyography (EMG) and mechanomyography (MMG) activities of muscles, there is no method to systematically quantify the temporal alignment between corresponding EMG and MMG signals. We proposed a novel method to determine the level of coincident activity in quasi-periodic MMG and EMG signals. The method optimizes 3 muscle-specific parameters: amplitude threshold, window size and minimum percent of EMG and MMG overlap using a particle swarm optimization algorithm to maximize the agreement (balanced accuracy) between electrical and mechanical muscle activity. The method was applied to bilaterally recorded EMG and MMG signals from 4 lower limb muscles per side of 25 pediatric participants during self-paced gait. Mean balanced accuracy exceeded 75% for all muscles except the lateral gastrocnemius, where EMG and MMG misalignment was notable (56% balanced accuracy). The proposed method can be applied to the criterion-driven comparison of simultaneously recorded myographic signals from two different measurement modalities during a motor task.

Comparing electro- and mechano-myographic muscle activation patterns in self-paced pediatric gait.

Electromyography (EMG) is the standard modality for measuring muscle activity. However, the convenience and availability of low-cost accelerometer-based wearables makes mechanomyography (MMG) an increasingly attractive alternative modality for clinical applications. Literature to date has demonstrated a strong association between EMG and MMG temporal alignment in isometric and isokinetic contractions. However, the EMG-MMG relationship has not been studied in gait. In this study, the concurrence of EMG- and MMG-detected contractions in the tibialis anterior, lateral gastrocnemius, vastus lateralis, and biceps femoris muscles were investigated in children during self-paced gait. Furthermore, the distribution of signal power over the gait cycle was statistically compared between EMG-MMG modalities. With EMG as the reference, muscular contractions were detected based on MMG with balanced accuracies between 88 and 94% for all muscles except the gastrocnemius. MMG signal power differed from that of EMG during certain phases of the gait cycle in all muscles except the biceps femoris. These timing and power distribution differences between the two modalities may in part be related to muscle fascicle length changes that are unique to muscle motion during gait. Our findings suggest that the relationship between EMG and MMG appears to be more complex during gait than in isometric and isokinetic contractions.

Wrist rotations about one or two axes affect maximum wrist strength.

Most wrist strength studies evaluate strength about one axis, and postural deviations about that same axis. The purpose of this study was to determine if wrist posture deviations about one axis (e.g. flexion/extension), or two axes (e.g. flexion/extension and pronation/supination), affect the strength about another axis (e.g. ulnar deviation). A custom-built instrumented handle was used to measure maximum static isometric torque exertions at 18 wrist postures (combinations of flexion/extension, radial/ulnar deviation, and pronation/supination). Ulnar deviation torques were highest when the wrist was in neutral. This pattern was not maintained for the other torque directions; the generated torque tended to be highest when the wrist posture was not neutral. The effects were similar for male and female subjects, although male subjects exerted significantly larger torques in all directions. This study illustrates that there is a complex relationship between wrist posture and maximal wrist torques.