The musculo-skeletal response of athletes to various activities during training exercises has become a critical issue in order to optimize their performance and minimize injuries. However, dynamic and kinematic measures of an athlete’s activity are generally limited by constraints in data collection and technology. Thus, the choice of reliable and accurate sensors is crucial for gathering data in indoor and outdoor conditions. The aim of this study is to validate the use of the accelerometer of a high sampling rate ( $1344\mathrm{Hz}$ ) Inertial Measurement Unit (IMU) in the frame of running activities. To this end, two validation protocols are imposed: a classical one on a shaker, followed by another one during running, the IMU being attached to a test subject. For each protocol, the response of the IMU Accelerometer (IMUA) is compared to a calibrated industrial accelerometer, considered as the gold standard for dynamic and kinematic data collection. The repeatability, impact of signal frequency and amplitude (on shaker) as well as the influence of speed (while running) are investigated. Results reveal that the IMUA exhibits good repeatability. Coefficient of Variation CV is $1\%\left(8.58,\pm ,0.06,,\mathrm{m},/,{\mathrm{s}}^2\right)$ on the shaker and $3\%\left(26.65,\pm ,0.69,,\mathrm{m},/,{\mathrm{s}}^2\right)$ while running. However, the shaker test shows that the IMUA is affected by the signal frequency (error exceeds $10\%$ beyond $80\mathrm{Hz}$ ), an observation confirmed by the running test. Nevertheless, the IMUA provides a reliable measure in the range 0–100 Hz, i.e., the most relevant part in the energy spectrum over the range 0–150 Hz during running. In our view, these findings emphasize the validity of IMUs for the measurement of acceleration during running.

Smart walkers are commonly used as potential gait assistance devices, to provide physical and cognitive assistance within rehabilitation and clinical scenarios. To understand such rehabilitation processes, several biomechanical studies have been conducted to assess human gait with passive and active walkers. Several sessions were conducted with 11 healthy volunteers to assess three interaction strategies based on passive, low and high mechanical stiffness values on the AGoRA Smart Walker. The trials were carried out in a motion analysis laboratory. Kinematic data were also collected from the smart walker sensory interface. The interaction force between users and the device was recorded. The force required under passive and low stiffness modes was $56.66\%$ and $67.48\%$ smaller than the high stiffness mode, respectively. An increase of $17.03\%$ for the hip range of motion, as well as the highest trunk’s inclination, were obtained under the resistive mode, suggesting a compensating motion to exert a higher impulse force on the device. Kinematic and physical interaction data suggested that the high stiffness mode significantly affected the users’ gait pattern. Results suggested that users compensated their kinematics, tilting their trunk and lower limbs to exert higher impulse forces on the device.

Exoskeletons have been assessed by qualitative and quantitative features known as performance indicators. Within these, the ergonomic indicators have been isolated, creating a lack of methodologies to analyze and assess physical interfaces. In this sense, this work presents a three-dimensional relative motion assessment method. This method quantifies the difference of orientation between the user’s limb and the exoskeleton link, providing a deeper understanding of the Human–Robot interaction. To this end, the AGoRA exoskeleton was configured in a resistive mode and assessed using an optoelectronic system. The interaction quantified a difference of orientation considerably at a maximum value of 41.1 degrees along the sagittal plane. It extended the understanding of the Human–Robot Interaction throughout the three principal human planes. Furthermore, the proposed method establishes a performance indicator of the physical interfaces of an exoskeleton.

Amplified by the development of new technologies, the interest in personal performance has been growing over the last years. Acceleration has proved to be an easy variable to collect, and was addressed in several works. However, few of them evaluate the effect of running speed on relevant indicators. The influence of the sensors location on the measurement is rarely studied as well. This study is dedicated to investigating the effect of running speed on acceleration measured at three different positions on 18 volunteers. All participants were equipped with three inertial measurement units: on the dorsal surface of the right foot (Fo), at the centre of gravity of the tibia (Ti), at the L4-L5 lumbar (Lu). The test was performed on a treadmill at nine randomised speeds between 8 and 18 km/h. Ten accelerometric variables were calculated. Linear regressions were used to calculate speed from the indicators calculated on (Lu), (Ti), (Fo). Indicators associated to signal energy were highly correlated with speed ( $r^2>0.90$). Median frequency appears to be affected by the frequency resolution. Finally, the measurement points closest to the impact zone result in the most correlated indicators.

Recently the use of Inertial Measurement Units (IMU's) has been extended to several applications in human activity. In running, several studies show the possibility of using IMU's to measure different indicators of speed and foot strike. However, few studies describe the repeatability of those indicators. In this context, the aim of this study is to analyse the intra and inter test repeatability of several temporal and spectral indicators using an IMU under constant running conditions. Accelerations were measured using three IMU's mounted on the trunk near the lumbar, the right tibia and the dorsal surface of the right shoe above the metatarsals. The subject follows two different protocols to realize the intra test and the inter test repeatability of eight different parameters: root mean square (RMS) values of acceleration, kurtosis, total energy, median frequency, mechanical stiffness, mean stride duration, contact and flying duration. For all parameters the mean, standard deviation and coefficient of variation were computed for each set of test. The coefficient of variation was lower than 5% for both test for all parameters except kurtosis and the median frequency. Parameters with acceptable value at constant conditions of surface and speed can be used as an indicator to compare several conditions, such as the influence of speed, surface or anthropometry of the subjects

Although accelerometers’ responses during running are not perfectly understood, they are widely used to study performance and the risk of injury. To outline the typical tibial acceleration pattern during running, this study aims to investigate the repeatability of acceleration signals with respect to the ground reaction force waveforms. Ten amateur runners were asked to perform ten trials along a straight line. One participant was asked to perform this protocol over ten sessions. Tibial accelerations and ground reaction forces were measured during the stance phase. The coefficient of multiple correlation R was computed to study the intra- and inter-test and subject repeatability of accelerometric and force waveforms. A good (R>0.8) intra- and inter-test repeatability was observed for all measured signals. Similar results were observed for intra-subject repeatability. A good inter-subject repeatability was observed only for the longitudinal acceleration and vertical and antero-posterior forces. Typical accelerometric signatures were outlined for each case studied.