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Manual wheelchair (MWC) locomotion exposes the user's upper-body to large and repetitive loads, which can lead to upper limbs pain and injuries. A thinner understanding of the influence of MWC settings on propulsion biomechanics could allow for a better adaptation of MWC configuration to the user, thus limiting the risk of developing such injuries. Advantageously compared to experimental studies, simulation methods allow numerous configurations to be tested. Recent studies have developed predictive locomotion simulation using optimal control methods. However, those models do not consider MWC anteroposterior stability, potentially resulting in unreasonable propulsion strategies. To this extent, this study aimed at confirming if constraining MWC anteroposterior stability in the optimal control formulation could lead to a different simulated movement. For this purpose, a four-link rigid-body system was used in a forward dynamics optimization paired with an anteroposterior stability constraint to predict MWC locomotion dynamics of the upper limbs during both startup and steady-state propulsion. Simulation results indicated the occurrence of MWC tipping when stability was not constrained, and that the constrained optimal control algorithm predicted different propulsion strategies. Hence, further proceedings of MWC locomotion simulation and optimal control investigations should take the anteroposterior stability into account to achieve more realistic simulations. Additionally, the implementation of the anteroposterior stability constrains unexpectedly resulted in a reduction of the computational time., (Copyright © 2023 by ASME.)

During manual wheelchair (MWC) locomotion, the user's upper limbs are subject to heavy stresses and fatigue because the upper body is permanently engaged to propel the MWC. These stresses and fatigue vary according to the environmental barriers encountered outdoors along a given path. This study aimed at conducting a systematic review of the literature assessing the biomechanics of MWC users crossing various situations, which represent physical environmental barriers. Through a systematic search on PubMed, 34 articles were selected and classified according to the investigated environmental barriers: slope; cross-slope; curb; and ground type. For each barrier, biomechanical parameters were divided into four categories: spatiotemporal parameters; kinematics; kinetics; and muscle activity. All results from the different studies were gathered, including numerical data, and assessed with respect to the methodology used in each study. This review sheds light on the fact that certain situations (cross-slopes and curbs) or parameters (kinematics) have scarcely been studied, and that a wider set of situations should be studied. Five recommendations were made at the end of this review process to standardize the procedure when reporting materials, methods, and results for the study of biomechanics of any environmental barrier encountered in MWC locomotion: (i) effectively reporting barriers' lengths, grades, or heights; (ii) striving for standardization or a report of the approach conditions of the barrier, such as velocity, especially on curbs; (iii) reporting the configuration of the used MWC, and if it was fitted to the subject's morphology; (iv) reporting rotation sequences for the expression of moments and kinematics, and when used, the definition of the musculoskeletal model; lastly (v) when possible, reporting measurement uncertainties and model reconstruction errors., Competing Interests: The authors have declared that no competing interests exist.

Background: The analysis of biomechanical parameters derived from the body center of mass (BCoM) 3D motion allows for the characterization of gait impairments in people with lower-limb amputation, assisting in their rehabilitation. In this context, magneto-inertial measurement units are promising as they allow to measure the motion of body segments, and therefore potentially of the BCoM, directly in the field. Finding a compromise between the accuracy of computed parameters and the number of required sensors is paramount to transfer this technology in clinical routine., Research Question: Is there a reduced subset of instrumented segments (BSN) allowing a reliable and accurate estimation of the 3D BCoM acceleration transfemoral amputees?, Methods: The contribution of each body segment to the BCoM acceleration was quantified in terms of weight and similarity in ten people with transfemoral amputation. First, body segments and BCoM accelerations were obtained using an optoelectronic system and a full-body inertial model. Based on these findings, different scenarios were explored where the use of one sensor at pelvis/trunk level and of different networks of segment-mounted sensors for the BCoM acceleration estimation was simulated and assessed against force plate-based reference acceleration., Results: Trunk, pelvis and lower-limb segments are the main contributors to the BCoM acceleration in transfemoral amputees. The trunk and shanks BSN allows for an accurate estimation of the sagittal BCoM acceleration (Normalized RMSE ≤ 13.1 %, Pearson's correlations r ≥ 0.86), while five segments are necessary when the 3D BCoM acceleration is targeted (Normalized RMSE ≤ 13.2 %, Pearson's correlations r ≥ 0.91)., Significance: A network of three-to-five segments (trunk and lower limbs) allows for an accurate estimation of 2D and 3D BCoM accelerations. The use of a single pelvis- or trunk-mounted sensor does not seem advisable. Future studies should be performed to confirm these results where inertial sensor measured accelerations are considered., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The analysis of the body center of mass (BCoM) 3D kinematics provides insights on crucial aspects of locomotion, especially in populations with gait impairment such as people with amputation. In this paper, a wearable framework based on the use of different magneto-inertial measurement unit (MIMU) networks is proposed to obtain both BCoM acceleration and velocity. The proposed framework was validated as a proof of concept in one transfemoral amputee against data from force plates (acceleration) and an optoelectronic system (acceleration and velocity). The impact in terms of estimation accuracy when using a sensor network rather than a single MIMU at trunk level was also investigated. The estimated velocity and acceleration reached a strong agreement (ρ > 0.89) and good accuracy compared to reference data (normalized root mean square error (NRMSE) < 13.7%) in the anteroposterior and vertical directions when using three MIMUs on the trunk and both shanks and in all three directions when adding MIMUs on both thighs (ρ > 0.89, NRMSE ≤ 14.0% in the mediolateral direction). Conversely, only the vertical component of the BCoM kinematics was accurately captured when considering a single MIMU. These results suggest that inertial sensor networks may represent a valid alternative to laboratory-based instruments for 3D BCoM kinematics quantification in lower-limb amputees.

Purpose: Daily locomotion with a manual wheelchair includes curvilinear movements. However, little is known about the resisting forces in play during turning manoeuvres where the wheels are generally both rolling and swivelling. This study aimed at quantifying the swivelling resistance parameters of several wheels on different surfaces and to evaluate the effect of the curvature radius on these parameters., Materials and Methods: A specific test bench was designed allowing the swivelling resistance parameters of a wheel rolling while swivelling to be determined. Seven wheels (3 front and 4 rear wheels), three surfaces (plywood, linoleum and carpet), two loads (25 and 45 kg) and five curvature radii (from 0 to 0.4 m) were tested through a full factorial design experiment., Results: Results showed that the wheel type was the most influential factor on swivelling resistance parameters, followed by the surface and the curvature radius. The effect of the load on swivelling resistance parameters was found negligible when compared to the influence of other factors. A predictive model for swivelling resistance parameters of the different wheel/surface combinations was proposed, as a function of the curvature radius., Conclusion: This study allowed the swivelling resistance parameters of different wheel/surface combinations to be quantified, as a function of the curvature radius of the wheel trajectory. Combined with data on rolling resistance, these data could now be used to assess energy losses during real life ambulation or to achieve more realistic behaviour in virtual rehabilitation environment.Implications for rehabilitationSwivelling resistances are increased by carpet surfaces compared to tile surfaces.Conversely to rolling resistance, castors wheels are less prone to swivelling resistance than rear wheelsThe swivelling resistance of a wheel rolling while swivelling is decreased compared to a pure swivelling movement.Combined with data on rolling resistance, these data on swivelling resistance would allow energy loss during daily life activity to be determined or as input data for the control of wheelchair simulator in virtual environment used for rehabilitation.

Purpose: During manual wheelchair (MWC) skill acquisition, users adapt their propulsion technique through changes in biomechanical parameters. This evolution is assumed to be driven towards a more efficient behavior. However, when no specific training protocol is provided to users, little is known about how they spontaneously adapt during overground MWC locomotion. For that purpose, we investigated this biomechanical spontaneous adaptation within the initial phase of low-intensity uninstructed training. Materials and methods: Eighteen novice able-bodied subjects were enrolled to perform 120 min of uninstructed practice with a field MWC, distributed over 4 weeks. Subjects were tested during the very first minutes of the program, and after completion of the entire training protocol. Spatiotemporal parameters, handrim forces, motor force, rolling resistance and fore-aft stability were investigated using an instrumented field wheelchair. Results: Participants rapidly increased linear velocity of the MWC, thanks to a higher propulsive force. This was achieved thanks to higher handrim forces, combined with an improved fraction of effective force for startup but not for propulsion. Despite changes in mechanical actions exerted by the user on the MWC, rolling resistance remained constant but the stability index was noticeably altered. Conclusion: Even if no indication is given, novice MWC users rapidly change their propulsion technique and increase their linear speed. Such improvements in MWC mobility are allowed by a mastering of the whole range of stability offered by the MWC, which raises the issue of safety on the MWC.Implications for rehabilitationThe learning process of manual wheelchair locomotion induces adaptations for novice users, who change their propulsion technique to improve their mobility.Several wheelchair biomechanical parameters change during the learning process, especially wheelchair speed, handrim forces, motor force, rolling resistance and fore-aft stability.Fore-aft stability on the wheelchair rapidly reached the tipping limits for users. Technical solutions that preserve stability but do not hinder mobility have to beimplemented, for instance by adding anti-tipping wheels rather than moving the seat forwards with respect to the rear wheels axle.

In recent years, inertial measurement units (IMUs) have been proposed as an alternative to force platforms and pressure sensors for gait events (i.e., initial and final contacts) detection. While multiple algorithms have been developed, the impact of gait event timing errors on temporal parameters and asymmetry has never been investigated in people with transfemoral amputation walking freely on level ground. In this study, five algorithms were comparatively assessed on gait data of seven people with transfemoral amputation, equipped with three IMUs mounted at the pelvis and both shanks, using pressure insoles for reference. Algorithms' performance was first quantified in terms of gait event detection rate (sensitivity, positive predictive value). Only two algorithms, based on shank mounted IMUs, achieved an acceptable detection rate (positive predictive value > 99%). For these two, accuracy of gait events timings, temporal parameters, and absolute symmetry index of stance-phase duration (SPD-ASI) were assessed. Whereas both algorithms achieved high accuracy for stride duration estimates (median errors: 0%, interquartile ranges < 1.75%), lower accuracy was found for other temporal parameters due to relatively high errors in the detection of final contact events. Furthermore, SPD-ASI derived from IMU-based algorithms proved to be significantly different to that obtained from insoles data. Graphical abstract Gait event detection with IMU in people with transfemoral amputation: initial contact (IC) and final contact (FC) events at the sound (s) and prosthetic (p) side are identified. Five algorithms were implemented using either shank-mounted or pelvis-mounted IMUs. Gait events were used to estimate temporal parameters (stride duration, stance phase duration [SPD], and double support time) and SPD asymmetry.

Multibody kinematic optimization is frequently used to assess shoulder kinematics during manual wheelchair (MWC) propulsion, but multiple kinematics chains are available. It is hypothesized that these different kinematic chains affect marker tracking, shoulder kinematics, and resulting musculotendon (MT) lengths. In this study, shoulder kinematics and MT lengths obtained from four shoulder kinematic chains (open-loop thorax-clavicle-scapula-humerus (M1), closed-loop with contact ellipsoid (M2), scapula rhythm from regression equations (M3), and a single ball-and- socket joint between the thorax and the humerus (M4) were compared. Right-side shoulder kinematics from seven subjects were obtained with 34 reflective markers and a scapula locator using an optoelectronic motion capture system while propelling on a MWC simulator. Data were processed based on the four models. The results showed the impact of shoulder kinematic chains on all studied variables. Marker reconstruction errors were found to be similar between M1 and M2 and lower than for M3 and M4. Few degrees-of-freedom (DoF) were noticeably different between M1 and M2, but all shoulder DoFs were significantly affected between M1 and M4. As a consequence of differences in joint kinematics, MT lengths were affected by the kinematic chain definition. The contact ellipsoid (M2) was found as a good trade-off between marker tracking and penetration avoidance of the scapula. The regression-based model (M3) was less efficient due to limited humerus elevation during MWC propulsion, as well as the ball-and-socket model (M4) which appeared not suitable for upper limbs activities, including MWC propulsion., (Copyright © 2019 by ASME.)

Several kinematic chains of the upper limbs have been designed in musculoskeletal models to investigate various upper extremity activities, including manual wheelchair propulsion. The aim of our study was to compare the effect of an ellipsoid mobilizer formulation to describe the motion of the scapulothoracic joint with respect to regression-based models on shoulder kinematics, shoulder kinetics and computational time, during manual wheelchair propulsion activities. Ten subjects, familiar with manual wheelchair propulsion, were equipped with reflective markers and performed start-up and propulsion cycles with an instrumented field wheelchair. Kinematic data obtained from the optoelectronic system and kinetic data measured by the sensors on the wheelchair were processed using the OpenSim software with three shoulder joint modeling versions (ellipsoid mobilizer, regression equations or fixed scapula) of an upper-limb musculoskeletal model. As expected, the results obtained with the three versions of the model varied, for both segment kinematics and shoulder kinetics. With respect to the model based on regression equations, the model describing the scapulothoracic joint as an ellipsoid could capture the kinematics of the upper limbs with higher fidelity. In addition, the mobilizer formulation allowed to compute consistent shoulder moments at a low computer processing cost. Further developments should be made to allow a subject-specific definition of the kinematic chain., (Copyright © 2019. Published by Elsevier Ltd.)

Purpose: Wheelchair locomotion is constraining for the upper limbs and involves a set of motor tasks that need to be learnt by a novice user. To understand this integration process, we investigated the evolution of shoulder kinetics during start-up and propulsion within the initial phase of low-intensity uninstructed training., Materials and Methods: Seventeen novice able-bodied subjects performed a 120-min uninstructed practice distributed over 4 weeks. During the initial and final sessions, upper limbs kinematics and hand-rim kinetics were continuously collected. Inverse kinematics and dynamics coupled to a three-dimensional linked-segment model were used to compute shoulder net moments., Results: Participants increased the speed of the wheelchair with practice. In average, an increase of shoulder net moments and mechanical work during the push phase was observed. Conversely, during the recovery phase, participants slightly increased shoulder power but maintained a similar level of shoulder loading. However, individual evolutions allowed the definition of two groups defined as: "increasers", who increased shoulder loading and mechanical work versus "decreasers", who managed to limit shoulder loading while improving the wheelchair speed., Conclusion: These findings underline that individual adaptation strategies are essential to take into account when designing a rehabilitation protocol for wheelchair users. Implications for Rehabilitation The learning process of manual wheelchair locomotion is essential for the assimilation of motor tasks leading individuals to select their propulsion technique. Novice users display different learning strategies: some people increase shoulder loading very early but others spontaneously manage to increase the wheelchair speed while maintaining a constant level of shoulder loading. Wheelchair rehabilitation programs should be individualized to take into account the subject-specific learning strategy.

Purpose: Among the different resistances occurring during wheelchair locomotion and that limit the user autonomy, bearing resistance is generally neglected, based on a few studies carried out in static conditions and by manufacturer's assertion. Therefore, no special attention is generally paid to the mounting and the maintenance of manual wheelchair bearings. However, the effect of inadequate mounting or maintenance on wheelchair bearing resistance has still to be clarified. This study aimed at filling this gap by developing and validating a specific device allowing the measurement of wheelchair bearing friction, characterized by low speed velocities, with an accuracy lower than 0.003 Nm., Methods: The bearing resistance measured by the device was compared to free deceleration measurement, intra and inter operator reproducibility were assessed. A factorial experiment allowed the effects of various functioning parameters (axial and radial loads, velocity) to be classified., Results: The device allowed significant differences in the bearing resistance of static and rotating conditions to be measured, even if a relatively high proportionality was found between both conditions. The factorial experiment allowed the expected impact of the radial load on bearing resistance as well as the predominant effect of the axial load to be demonstrated., Conclusions: As a consequence, it appeared that the control of the axial load is compulsory for measurement purposes or during wheel mounting, to avoid significant increase of global resistance during wheelchair locomotion. The findings of this study could help enhancing the models which assess manual wheelchair mechanical power from its settings and use conditions.

This article presents an examination and validation of a method to measure the field deceleration of a manual wheelchair (MWC) and to calculate the rolling resistances properties of the front and rear wheels. This method was based on the measurements of the MWC deceleration for various load settings from a 3D accelerometer. A mechanical model of MWC deceleration was developed which allowed computing the rolling resistance factors of front and rear wheels on a tested surface. Four deceleration sets were conducted on two paths on the same ground to test the repeatability. Two other deceleration sets were conducted using different load settings to compute the rolling resistance parameters (RPs). The theoretical decelerations of three load settings were computed and compared with the measured decelerations. The results showed good repeatability (variations of measures represented 6-11% of the nominal values) and no statistical difference between the path results. The rolling RPs were computed and their confidence intervals were assessed. For the last three sets, no significant difference was found between the theoretical and measured decelerations. This method can determine the specific rolling resistance properties of the wheels of a MWC, and be employed to establish a catalogue of the rolling resistance properties of wheels on various surfaces.

This article proposes a simple and convenient method for assessing the subject-specific rolling resistance acting on a manual wheelchair, which could be used during the provision of clinical service. This method, based on a simple mathematical equation, is sensitive to both the total mass and its fore-aft distribution, which changes with the subject, wheelchair properties, and adjustments. The rolling resistance properties of three types of front casters and four types of rear wheels were determined for two indoor surfaces commonly encountered by wheelchair users (a hard smooth surface and carpet) from measurements of a three-dimensional accelerometer during field deceleration tests performed with artificial load. The average results provided by these experiments were then used as input data to assess the rolling resistance from the mathematical equation with an acceptable accuracy on hard smooth and carpet surfaces (standard errors of the estimates were 4.4 and 3.9 N, respectively). Thus, this method can be confidently used by clinicians to help users make trade-offs between front and rear wheel types and sizes when choosing and adjusting their manual wheelchair.