The effects of an upper limb exoskeleton on gait performance and stability.

Upper limb exoskeletons (ULEs) are emerging as workplace tools to alleviate workload and prevent work-related musculoskeletal disorders during lifting tasks. However, their introduction raises concerns about potential instability and increased fall risk for workers. This study investigates gait performance and stability parameters implications of ULE use. Fifteen participants performed a carrying task with different loads (0, 5, 10, 15 kg), both with and without the use of an ULE. Spatiotemporal gait parameters, Required Coefficient of Friction (RCoF), Minimum Foot Clearance (MFC), and Margin of Stability (MoS) were analysed. The findings indicate that while the ULE does not significantly alter most gait parameters or slip risk, it may negatively impact trip risk. Furthermore, while mediolateral stability remains unaffected, anteroposterior stability is compromised by ULE usage. These insights are critical for ensuring the safe implementation of ULEs in occupational settings.

A Method for Quantifying Back Flexion/Extension from Three Inertial Measurement Units Mounted on a Horse's Withers, Thoracolumbar Region, and Pelvis.

Back mobility is a criterion of well-being in a horse. Veterinarians visually assess the mobility of a horse's back during a locomotor examination. Quantifying it with on-board technology could be a major breakthrough to help them. The aim of this study was to evaluate the accuracy of a method of quantifying the back mobility of horses from inertial measurement units (IMUs) compared to motion capture (MOCAP) as a gold standard. Reflective markers and IMUs were positioned on the withers, eighteenth thoracic vertebra, and pelvis of four sound horses. The horses performed a walk and trot in straight lines and performed a gallop in circles on a soft surface. The developed method, based on the three IMUs, consists of calculating the flexion/extension angle of the thoracolumbar region. The IMU method showed a mean bias of 0.8° (±1.5°) (mean (±SD)) and 0.8° (±1.4°), respectively, for the flexion and extension movements, all gaits combined, compared to the MOCAP method. The results of this study suggest that the developed method has a similar accuracy to that of MOCAP, opening up possibilities for easy measurements under field conditions. Future studies will need to examine the correlations between these biomechanical measures and clinicians' visual assessment of back mobility defects.

Development of a Methodology for Low-Cost 3D Underwater Motion Capture: Application to the Biomechanics of Horse Swimming.

Hydrotherapy has been utilized in horse rehabilitation programs for over four decades. However, a comprehensive description of the swimming cycle of horses is still lacking. One of the challenges in studying this motion is 3D underwater motion capture, which holds potential not only for understanding equine locomotion but also for enhancing human swimming performance. In this study, a marker-based system that combines underwater cameras and markers drawn on horses is developed. This system enables the reconstruction of the 3D motion of the front and hind limbs of six horses throughout an entire swimming cycle, with a total of twelve recordings. The procedures for pre- and post-processing the videos are described in detail, along with an assessment of the estimated error. This study estimates the reconstruction error on a checkerboard and computes an estimated error of less than 10 mm for segments of tens of centimeters and less than 1 degree for angles of tens of degrees. This study computes the 3D joint angles of the front limbs (shoulder, elbow, carpus, and front fetlock) and hind limbs (hip, stifle, tarsus, and hind fetlock) during a complete swimming cycle for the six horses. The ranges of motion observed are as follows: shoulder: 17 ± 3°; elbow: 76 ± 11°; carpus: 99 ± 10°; front fetlock: 68 ± 12°; hip: 39 ± 3°; stifle: 68 ± 7°; tarsus: 99 ± 6°; hind fetlock: 94 ± 8°. By comparing the joint angles during a swimming cycle to those observed during classical gaits, this study reveals a greater range of motion (ROM) for most joints during swimming, except for the front and hind fetlocks. This larger ROM is usually achieved through a larger maximal flexion angle (smaller minimal angle of the joints). Finally, the versatility of the system allows us to imagine applications outside the scope of horses, including other large animals and even humans.

Quantified analysis of facial movement: A reference for clinical applications.

Most techniques for evaluating unilateral impairments in facial movement yield subjective measurements. The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1-M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1-M5, and displacement patterns were defined. The patients and age-matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof-of-concept experiments, we collected quantitative data on patients with facial palsy and created a patient-specific radar plot. Our new protocol for clinical facial motion capture ("quantified analysis of facial movement," QAFM) was accurate and should thus facilitate the long-term clinical follow-up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. The patient-specific radar plot enables clinicians to read and understand the results rapidly.

Scoring the Sit-to-Stand Performance of Parkinson's Patients with a Single Wearable Sensor.

Monitoring disease progression in Parkinson's disease is challenging. Postural transfers by sit-to-stand motions are adapted to trace the motor performance of subjects. Wearable sensors such as inertial measurement units allow for monitoring motion performance. We propose quantifying the sit-to-stand performance based on two scores compiling kinematics, dynamics, and energy-related variables. Three groups participated in this research: asymptomatic young participants (n = 33), senior asymptomatic participants (n = 17), and Parkinson's patients (n = 20). An unsupervised classification was performed of the two scores to differentiate the three populations. We found a sensitivity of 0.4 and a specificity of 0.96 to distinguish Parkinson's patients from asymptomatic subjects. In addition, seven Parkinson's patients performed the sit-to-stand task "ON" and "OFF" medication, and we noted the scores improved with the patients' medication states (MDS-UPDRS III scores). Our investigation revealed that Parkinson's patients demonstrate a wide spectrum of mobility variations, and while one inertial measurement unit can quantify the sit-to-stand performance, differentiating between PD patients and healthy adults and distinguishing between "ON" and "OFF" periods in PD patients is still challenging.

The Protraction and Retraction Angles of Horse Limbs: An Estimation during Trotting Using Inertial Sensors.

The protraction and retraction angles of horse limbs are important in the analysis of horse locomotion. This study explored two methods from an IMU positioned on the canon bone of eight horses to estimate these angles. Each method was based on a hypothesis in order to define the moment corresponding with the verticality of the canon bone: (i) the canon bone is in a vertical position at 50% of the stance phase or (ii) the verticality of the canon bone corresponds with the moment when the horse's withers reach their lowest point. The measurements were carried out on a treadmill at a trot and compared with a standard gold method based on motion capture. For the measurement of the maximum protraction and retraction angles, method (i) had average biases (0.7° and 1.7°) less than method (ii) (-1.3° and 3.7°). For the measurement of the protraction and retraction angles during the stance phase, method (i) had average biases (4.1° and -3.3°) higher to method (ii) (2.1° and -1.3°). This study investigated the pros and cons of a generic method (i) vs. a specific method (ii) to determine the protraction and retraction angles of horse limbs by a single IMU.

Using accelerations of single inertial measurement units to determine the intensity level of light-moderate-vigorous physical activities: Technical and mathematical considerations.

Quantifying physical activity and estimating the metabolic equivalent of tasks based on inertial measurement units has led to the emergence of multiple methods and data reduction approaches known as physical activity metrics. The present study aims to compare those metrics and reduction approaches based on descriptive and high order statistics. Data were obtained from 147 young healthy subjects wearing inertial measurement units at their wrist or ankle during standing, walking and running, labeled as light, medium or vigorous activities. The research question was, first, if those metrics allowed differentiating between light, moderate, and vigorous physical activities, and, secondly, what was the relationship with the metabolic equivalent of the task performed. The results showed that each metric differentiated the level of activity and presented a high correlation with the metabolic equivalent of the task. However, each metric and data reduction approach demonstrated its specific statistical characteristics related to the localization of the sensors. Our findings also confirm the absolute necessity to detail explicitly all calculus and post processing of metrics in order to quantify the level of activity by inertial measurement units.

Comparison of Trotting Stance Detection Methods from an Inertial Measurement Unit Mounted on the Horse's Limb.

The development of on-board sensors, such as inertial measurement units (IMU), has made it possible to develop new methods for analyzing horse locomotion to detect lameness. The detection of spatiotemporal events is one of the keystones in the analysis of horse locomotion. This study assesses the performance of four methods for detecting Foot on and Foot off events. They were developed from an IMU positioned on the canon bone of eight horses during trotting recording on a treadmill and compared to a standard gold method based on motion capture. These methods are based on accelerometer and gyroscope data and use either thresholding or wavelets to detect stride events. The two methods developed from gyroscopic data showed more precision than those developed from accelerometric data with a bias less than 0.6% of stride duration for Foot on and 0.1% of stride duration for Foot off. The gyroscope is less impacted by the different patterns of strides, specific to each horse. To conclude, methods using the gyroscope present the potential of further developments to investigate the effects of different gait paces and ground types in the analysis of horse locomotion.

Optimal marker set assessment for motion capture of 3D mimic facial movements.

Nowadays, facial mimicry studies have acquired a great importance in the clinical domain and 3D motion capture systems are becoming valid tools for analysing facial muscles movements, thanks to the remarkable developments achieved in the 1990s. However, the face analysis domain suffers from a lack of valid motion capture protocol, due to the complexity of the human face. Indeed, a framework for defining the optimal marker set layout does not exist yet and, up to date, researchers still use their traditional facial point sets with manually allocated markers. Therefore, the study proposes an automatic approach to compute a minimum optimized marker layout to be exploited in facial motion capture, able to simplify the marker allocation without decreasing the significance level. Specifically, the algorithm identifies the optimal facial marker layouts selecting the subsets of linear distances among markers that allow to automatically recognizing with the highest performances, through a k-nearest neighbours classification technique, the acted facial movements. The marker layouts are extracted from them. Various validation and testing phases have demonstrated the accuracy, robustness and usefulness of the custom approach.

Design-validation of a hand exoskeleton using musculoskeletal modeling.

Exoskeletons are progressively reaching homes and workplaces, allowing interaction with virtual environments, remote control of robots, or assisting human operators in carrying heavy loads. Their design is however still a challenge as these robots, being mechanically linked to the operators who wear them, have to meet ergonomic constraints besides usual robotic requirements in terms of workspace, speed, or efforts. They have in particular to fit the anthropometry and mobility of their users. This traditionally results in numerous prototypes which are progressively fitted to each individual person. In this paper, we propose instead to validate the design of a hand exoskeleton in a fully digital environment, without the need for a physical prototype. The purpose of this study is thus to examine whether finger kinematics are altered when using a given hand exoskeleton. Therefore, user specific musculoskeletal models were created and driven by a motion capture system to evaluate the fingers' joint kinematics when performing two industrial related tasks. The kinematic chain of the exoskeleton was added to the musculoskeletal models and its compliance with the hand movements was evaluated. Our results show that the proposed exoskeleton design does not influence fingers' joints angles, the coefficient of determination between the model with and without exoskeleton being consistently high (R2¯=0.93) and the nRMSE consistently low (nRMSE¯ = 5.42°). These results are promising and this approach combining musculoskeletal and robotic modeling driven by motion capture data could be a key factor in the ergonomics validation of the design of orthotic devices and exoskeletons prior to manufacturing.

Evaluation of the kinetic energy of the torso by magneto-inertial measurement unit during the sit-to-stand movement.

Sit-to-stand tests are used in geriatrics as a qualitative issue in order to evaluate motor control and stability. In terms of measured indicators, it is traditionally the duration of the task that is reported, however it appears that the use of the kinetic energy as a new quantitative criterion allows getting a better understanding of musculoskeletal deficits of elderly subjects. The aim of this study was to determine the feasibility to obtain the measure of kinetic energy using magneto-inertial measurement units (MIMU) during sit-to-stand movements at various paces. 26 healthy subjects contributed to this investigation. Measured results were compared to a marker-based motion capture using the correlation coefficient and the normalized root mean square error (nRMSE). nRMSE were below 10% and correlation coefficients were over 0.97. In addition, errors on the mean kinetic energy were also investigated using Bland-Altman 95% limits of agreement (0.63 J-0.77 J), RMSE (0.29 J-0.38 J) and correlation coefficient (0.96-0.98). The results obtained highlighted that the method based on MIMU data could be an alternative to optoelectronic data acquisition to assess the kinetic energy of the torso during the sit-to-stand test, suggesting this method as being a promising alternative to determine kinetic energy during the sit-to-stand movement.

Human-Human Handover Tasks and How Distance and Object Mass Matter.

We investigated the coordination between two individuals during object handovers. Ten participants (eight males, two females; 26.0 ± 5.0 years, 72.7 ± 13.5 kg, 1.73 ± 0.8 m) arranged in pairs (a giver and a receiver), passed an object from the giver to the receiver at a self-selected speed. A motion capture system quantified the giver and the receiver's motion simultaneously. Three interpersonal distances and three object masses were chosen to study the handover. We hypothesized that (a) the handover occurs at half of the interpersonal distance between the giver and receiver and (b) the handover height depends on the objects' mass. Taken together, our results show that the handover strongly depends on the interpersonal distance between the giver and receiver, while object mass related only to handover duration.

Proposition, identification, and experimental evaluation of an inverse dynamic neuromusculoskeletal model for the human finger.

PURPOSE: The purpose of this study is to develop an inverse dynamic model of the human middle finger in order to identify the muscle activation, muscle force, and neural activation of the muscles involved during motion. Its originality comes from the coupling of biomechanical and physiological models and the proposition of a dedicated optimization procedure and cost function for identifying the model unknowns. METHODS: Three sub-models work in interaction: the first is the biomechanical model, primarily consisting of the dynamic equations of the middle finger system; the second is the muscle model, which helps to identify the muscle force from muscle activation and dynamic deformation for six involved muscles. The third model allows one to link muscle activation to neural intent from the Central Nervous System (CNS). This modeling procedure leads to a complex analytical nonlinear system identified using multi-step energy minimization procedure and a specific cost function. RESULTS: Numerical simulations with different articulation velocities are presented and discussed. Then, experimental evaluation of the proposed model is performed following a protocol combining electromyography and motion capture during a hand opening-closing paradigm. After comparison, several results from the simulation and experiments were found to be in accordance. The difficulty in evaluating such complex dynamic models is also demonstrated. CONCLUSIONS: Despite the model simplifications, the obtained preliminary results are promising. Indeed, the proposed model, once correctly validated in future works, should be a relevant tool to simulate and predict deficiencies of the middle finger system for rehabilitation purposes.