Background: Wearable magneto-inertial sensors are being increasingly used to obtain human motion measurements out of the lab, although their performance in applications requiring high accuracy, such as gait analysis, are still a subject of debate. The aim of this work was to validate a gait analysis system (H-Gait) based on magneto-inertial sensors, both in normal weight (NW) and overweight/obese (OW) subjects. The validation is performed against a reference multichannel recording system (STEP32), providing direct measurements of gait timings (through foot-switches) and joint angles in the sagittal plane (through electrogoniometers). Methods: Twenty-two young male subjects were recruited for the study (12 NW, 10 OW). After positioning body-fixed sensors of both systems, each subject was asked to walk, at a self-selected speed, over a 14-m straight path for 12 trials. Gait signals were recorded, at the same time, with the two systems. Spatio-temporal parameters, ankle, knee, and hip joint kinematics were extracted analyzing an average of 89 ± 13 gait cycles from each lower limb. Intraclass correlation coefficient and Bland-Altmann plots were used to compare H-Gait and STEP32 measurements. Changes in gait parameters and joint kinematics of OW with respect NW were also evaluated. Results: The two systems were highly consistent for cadence, while a lower agreement was found for the other spatio-temporal parameters. Ankle and knee joint kinematics is overall comparable. Joint ROMs values were slightly lower for H-Gait with respect to STEP32 for the ankle (by 1.9° for NW, and 1.6° for OW) and for the knee (by 4.1° for NW, and 1.8° for OW). More evident differences were found for hip joint, with ROMs values higher for H-Gait (by 6.8° for NW, and 9.5° for OW). NW and OW showed significant differences considering STEP32 (p = 0.0004), but not H-Gait (p = 0.06). In particular, overweight/obese subjects showed a higher cadence (55.0 vs. 52.3 strides/min) and a lower hip ROM (23.0° vs. 27.3°) than normal weight subjects. Conclusions: The two systems can be considered interchangeable for what concerns joint kinematics, except for the hip, where discrepancies were evidenced. Differences between normal and overweight/obese subjects were statistically significant using STEP32. The same tendency was observed using H-Gait.

Overweight/obesity is a physical condition that affects daily activities, including walking. The main purpose of this study was to identify if there is a relationship between body mass index (BMI) and gait characteristics in young adults. 12 normal weight (NW) and 10 overweight/obese (OW) individuals walked at a self-selected speed along a 14 m indoor path. H-Gait system, combining seven inertial sensors (fixed on pelvis and lower limbs), was used to record gait data. Walking speed, spatio-temporal parameters and joint kinematics in 3D were analyzed. Differences between NW and OW and correlations between BMI and gait parameters were evaluated. Conventional spatio-temporal parameters did not show statistical differences between the two groups or correlations with the BMI. However, significant results were pointed out for the joint kinematics. OW showed greater hip joint angles in frontal and transverse planes, with respect to NW. In the transverse plane, OW showed a greater knee opening angle and a shorter length of knee and ankle trajectories. Correlations were found between BMI and kinematic parameters in the frontal and transverse planes. Despite some phenomena such as soft tissue artifact and kinematics cross-talk, which have to be more deeply assessed, current results show a relationship between BMI and gait characteristics in young adults that should be looked at in osteoarthritis prevention.

The aim of this mini-review is to describe the potential application of surface electromyography (sEMG) techniques in aging studies. Aging is characterized by multiple changes of the musculoskeletal system physiology and function. This paper will examine some of the innovative methods used to monitor age-related alterations of the neuromuscular system from sEMG signals. A description of critical assumptions which underlie some of these approaches is emphasized. The first part focuses on the evolution of the recording techniques and describes some methodological issues. The second part focuses on how to use the following techniques to characterize aging: amplitude and spectral sEMG signal analysis, muscle fiber conduction velocity estimation, and myoelectric fatigue assessment. The last part describes a number of advanced sEMG approaches which seem promising in the geriatric population to estimate motor unit number, size, recruitment thresholds, and firing rates.

Monitoring surface electromyographic (EMG) signals can provide useful insights for characterizing muscle fatigue, which is defined as an exercise-induced strength loss. This experiment investigated the muscle fiber conduction velocity (CV) changes induced by an endurance run. The day before and immediately after a half-marathon run (21.097 km) 11 amateur runners performed maximum voluntary contractions (MVCs) of knee extensor muscles. During the MVC, multichannel EMG was recorded from the vastus lateralis and EMG amplitude and CV were calculated. After the run, knee extensors showed a decreased strength (−13 ± 9%, p = 0.001) together with a reduction in EMG amplitude (−13 ± 10%, p = 0.003) and in CV (−6 ± 8%, p = 0.032). Knee extensor strength loss positively correlated with vastus lateralis CV differences ( r = 0.76, p = 0.006). Thus, the exercises-induced muscle fatigue was associated not only with a decrease in EMG amplitude, but also with a reduction in CV. This finding suggests that muscle fibers with higher CV (i.e. those with greater fiber size) were the most impaired during strength production after an endurance run.