In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments.

In the last few decades, a number of technological developments have advanced the spread of wearable sensors for the assessment of human motion. These sensors have been also developed to assess athletes’ performance, providing useful guidelines for coaching, as well as for injury prevention. The data from these sensors provides key performance outcomes as well as more detailed kinematic, kinetic, and electromyographic data that provides insight into how the performance was obtained. From this perspective, inertial sensors, force sensors, and electromyography appear to be the most appropriate wearable sensors to use. Several studies were conducted to verify the feasibility of using wearable sensors for sport applications by using both commercially available and customized sensors. The present study seeks to provide an overview of sport biomechanics applications found from recent literature using wearable sensors, highlighting some information related to the used sensors and analysis methods. From the literature review results, it appears that inertial sensors are the most widespread sensors for assessing athletes’ performance; however, there still exist applications for force sensors and electromyography in this context. The main sport assessed in the studies was running, even though the range of sports examined was quite high. The provided overview can be useful for researchers, athletes, and coaches to understand the technologies currently available for sport performance assessment.

In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM) applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs) during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98) for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95) when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints.

Markerless human motion capture could be a potential tool for studying body biomechanics. Despite the extensive previous studies, the design of an accurate markerless system able to perform a quantitative clinical gait analysis is still an open challenge. Our purpose was to characterize the performance of a low-cost markerless system, consisting of the open-source library OpenPose, two webcams and a linear triangulation algorithm. The system was validated in terms of 3D kinematic gait analysis, by comparison with inertial sensors. Two synchronized videos of six healthy subjects were recorded in three webcam configurations, in walking and running sessions on a treadmill. Sagittal joint angles were compared between the two systems, to evaluate the kinematic performance of the markerless system. Results showed that the angular paths, provided by OpenPose, were close to the ones computed by inertial sensors in all camera positions, but OpenPose inaccuracy affected the computation of joint angles parameters producing absolute errors up to 14.0°± 1.8°. The observed differences depended on OpenPose ability in the recognition of joints centers and on camera configurations. In the optimal condition (joint visible from both cameras during the whole trial) our system accuracy resulted equal to 1.6 °± 0.3 °. This system could be useful in those applications where a real-time body tracking is required, i.e. video games or virtual rehabilitative trials. When a quantitative analysis is needed, the low level of accuracy may be overcome, by both increasing the cameras' number and implementing an optimization triangulation algorithm.

In the last years, several studies have been focused on understanding how the central nervous system controls muscles to perform a specific motor task. Although it still remains an open question, muscle synergies have come to be an appealing theory to explain the modular organization of the central nervous system. Even though the neural encoding of muscle synergies remains controversial, a large number of papers demonstrated that muscle synergies are robust across different tested conditions, which are within a day, between days, within a single subject, and between subjects that have similar demographic characteristics. Thus, muscle synergy theory has been largely used in several research fields, such as clinics, robotics, and sports. The present systematical review aims at providing an overview on the applications of muscle synergy theory in clinics, robotics, and sports; in particular, the review is focused on the papers that provide tangible information for (i) diagnosis or pathology assessment in clinics, (ii) robot-control design in robotics, and (iii) athletes’ performance assessment or training guidelines in sports.

This paper presents the modular design and control of a novel compliant lower limbmulti-joint exoskeleton for the rehabilitation of ankle kneemobility and locomotion of pediatric patients with neurological diseases, such as Cerebral Palsy (CP). The device consists of an untethered powered knee-ankle-foot orthosis (KAFO), addressed as WAKE-up (Wearable Ankle Knee Exoskeleton), characterized by a position control and capable of operating synchronously and synergistically with the human musculoskeletal system. The WAKE-up mechanical system, control architecture and feature extraction are described. Two test benches were used to mechanically characterize the device. The full system showed a maximum value of hysteresis equal to 8.8% and a maximum torque of 5.6 N m/rad. A pre-clinical use was performed, without body weight support, by four typically developing children and three children with CP. The aims were twofold: 1) to test the structure under weight-bearing conditions and 2) to ascertain its ability to provide appropriate assistance to the ankle and the knee during overground walking in a real environment. Results confirm the effectiveness of the WAKE-up design in providing torque assistance in accordance to the volitionalmovements especially in the recovery of correct foot landing at the start of the gait cycle.