An ISB-consistent Denavit-Hartenberg model of the human upper limb for joint kinematics optimization: validation on synthetic and robot data during a typical rehabilitation gesture.

Several biomedical contexts such as diagnosis, rehabilitation, and ergonomics require an accurate estimate of human upper limbs kinematics. Wearable inertial measurement units (IMU s) represent a suitable solution because of their unobtrusiveness, portability, and low-cost. However, the time-integration of the gyroscope angular velocity leads to an unbounded orientation drift affecting both angular and linear displacements over long observation interval. In this work, a Denavit-Hartenberg model of the upper limb was defined in accordance with the guidelines of the International Society of Biomechanics and exploited to design an optimization kinematics process. This procedure estimated the joint angles by minimizing the difference between the modelled and IMU-driven orientation of upper arm and forearm. In addition, reasonable constraints were added to limit the drift influence on the final joint kinematics accuracy. The validity of the procedure was tested on synthetic and experimental data acquired with a robotic arm over 20 minutes. Average rms errors amounted to 2.8 deg and 1.1 for synthetic and robot data, respectively. Clinical Relevance - The proposed method has the potential to improve robustness and accuracy of multi-joint kinematics estimation in the general contexts of home-based tele-rehabilitation interventions. In this respect adoption of multi-segmental kinematic model along with physiological joint constraints could contribute to address current limitations associated to unsupervised analysis in terms of monitoring and outcome assessment.

Estimating infant upper extremities motion with an RGB-D camera and markerless deep neural network tracking: A validation study.

Quantitative biomarkers of infant motion may be predictive of the development of movement disorders. This study presents and validates a low cost, markerless motion tracking method for the estimation of upper body kinematics of infants from which proper biomarkers may be extracted. The method requires a single RGB-D camera, a 2D motion tracking software publicly available (DeepLabCut) and an algorithm generating 3D point coordinates from the 2D tracked points, dealing with missing data, originating from various sources, for estimating joint kinematics. The proposed method is validated using known point kinematics obtained from a doll, with size and shape of an infant, lying on a turntable rotating at 33⅓ rpm. Two camera image plane orientations are tested: parallel to the turntable motion plane and forming a 45° angle with respect to the motion plane. The latter enhances the occurrence of body parts occlusions during motion as expected in live infant motion recordings. The length of upper body segments, elbow and shoulder joint angles and the linear point velocity determined with the proposed method are evaluated against reference values obtained from the known motion of the turntable. The relevant Mean Absolute Errors (MAE) found indicate the margin of error to expect when processing live infant motion. The proposed method may be improved if enhanced hardware and tracking software are employed, therefore reducing the above-mentioned margin of error. Clinical Relevance - The validation of the proposed method carried out in this study allows clinicians to select proper quantitative biomarkers obtained from infants upper body motion that may be useful for predicting movement disorders.

A wearable multi-sensor system for real world gait analysis.

Gait analysis is commonly performed in standardized environments, but there is a growing interest in assessing gait also in ecological conditions. In this regard, an important limitation is the lack of an accurate mobile gold standard for validating any wearable system, such as continuous monitoring devices mounted on the trunk or wrist. This study therefore deals with the development and validation of a new wearable multi-sensor-based system for digital gait assessment in free-living conditions. In particular, results obtained from five healthy subjects during lab-based and real-world experiments were presented and discussed. The in-lab validation, which assessed the accuracy and reliability of the proposed system, shows median percentage errors smaller than 2% in the estimation of spatio-temporal parameters. The system also proved to be easy to use, comfortable to wear and robust during the out-of-lab acquisitions, showing its feasibility for free-living applications.

Algorithms for Walking Speed Estimation Using a Lower-Back-Worn Inertial Sensor: A Cross-Validation on Speed Ranges.

Walking/gait speed is a key measure for daily mobility characterization. To date, various studies have attempted to design algorithms to estimate walking speed using an inertial sensor worn on the lower back, which is considered as a proper location for activity monitoring in daily life. However, these algorithms were rarely compared and validated on the same datasets, including people with different preferred walking speed. This study implemented several original, improved, and new algorithms for estimating cadence, step length and eventually speed. We designed comprehensive cross-validation to compare the algorithms for walking slow, normal, fast, and using walking aids. We used two datasets, including reference data for algorithm validation from an instrumented mat (40 subjects) and shanks-worn inertial sensors (88 subjects), with normal and impaired walking patterns. The results showed up to 50% performance improvements. Training of algorithms on data from people with different preferred speeds led to better performance. For the slow walkers, an average RMSE of 2.5 steps/min, 0.04 m, and 0.10 m/s were respectively achieved for cadence, step length, and speed estimation. For normal walkers, the errors were 3.5 steps/min, 0.08 m, and 0.12 m/s. An average RMSE of 1.3 steps/min, 0.05 m, and 0.10 m/s were also observed on fast walkers. For people using walking aids, the error significantly increased up to an RMSE of 14 steps/min, 0.18 m, and 0.27 m/s. The results demonstrated the robustness of the proposed combined speed estimation approach for different speed ranges. It achieved an RMSE of 0.10, 0.18, 0.15, and 0.32 m/s for slow, normal, fast, and using walking aids, respectively.

A method for gait events detection based on low spatial resolution pressure insoles data.

The accurate identification of initial and final foot contacts is a crucial prerequisite for obtaining a reliable estimation of spatio-temporal parameters of gait. Well-accepted gold standard techniques in this field are force platforms and instrumented walkways, which provide a direct measure of the foot-ground reaction forces. Nonetheless, these tools are expensive, non-portable and restrict the analysis to laboratory settings. Instrumented insoles with a reduced number of pressure sensing elements might overcome these limitations, but a suitable method for gait events identification has not been adopted yet. The aim of this paper was to present and validate a method aiming at filling such void, as applied to a system including two insoles with 16 pressure sensing elements (element area = 310 mm2), sampling at 100 Hz. Gait events were identified exploiting the sensor redundancy and a cluster-based strategy. The method was tested in the laboratory against force platforms on nine healthy subjects for a total of 801 initial and final contacts. Initial and final contacts were detected with low average errors of (about 20 ms and 10 ms, respectively). Similarly, the errors in estimating stance duration and step duration averaged 20 ms and <10 ms, respectively. By selecting appropriate thresholds, the method may be easily applied to other pressure insoles featuring similar requirements.

DoMoMEA: a Home-Based Telerehabilitation System for Stroke Patients.

After a cerebral stroke, survivors need to follow a neurorehabilitation program including exercises to be executed under a therapist's supervision or autonomously. Technological solutions are needed to support the early discharge of the patients just after the primary hospital treatments, by still providing an adequate level of rehabilitation. The DoMoMEA Project proposes a fully-wearable m-health solution able to administer a neurorehabilitation therapy in the patient's home or every other place established by the patient for a rehabilitation session. The exploitation of magneto-inertial measurement units only, wirelessly connected to an Android-operated device, provides robustness to different operating conditions and immunity to optical occlusion problems, compared to RGB-D cameras. Patients' engagement is fostered by the exploitation of the exergame version of the ten rehabilitation exercises, implemented in Unity 3D. Store-and-forward telemonitoring features, supported by cloud-based storage and by a web application accessible from anywhere by medical personnel and patients, enable constant transparent monitoring of the rehabilitation progresses. The clinical trial of the DoMoMEA telerehabilitation system will involve 40 post-stroke patients with mild impairment and will start as soon as the restrictions due to the COVID-19 pandemic will allow to enroll patients.

Gait changes following direct versus contralateral strength training: A randomized controlled pilot study in individuals with multiple sclerosis.

BACKGROUND: Contralateral strength training (CST) is increasingly investigated and employed as a non-conventional way to induce an indirect gain in strength in the weakened untrained limb. However, its effects on gait performance are more controversial. RESEARCH QUESTION: To assess and compare the effects of contralateral (CST) and direct (DST) strength training on spatio-temporal parameters, kinematic and kinetic descriptors of gait in persons with relapsing-remitting multiple sclerosis (PwMS). METHODS: Twenty-eight PwMS (EDSS 2.0-5.5) with inter-side difference in ankle dorsiflexors' strength ≥ 20 % and moderate gait impairment (walking speed 0.70-0.94 m/s), were randomly assigned to a CST (undergoing training of the less-affected dorsiflexors) or DST group (where the most-affected dorsiflexors were trained). Before and after a 6-week high-intensity resistance training (three 25-minute sessions/week), PwMS underwent bilateral measurements of dorsiflexors' maximal strength and assessment of gait spatio-temporal parameters, lower limb joint kinematics and kinetics. RESULTS AND SIGNIFICANCE: Following the training period, muscle strength increased significantly in both groups (on average, CST + 29.5 %, p < 0.0005; DST + 15.7 %, p = 0.001) with no difference between the two interventions. Significant changes in gait speed (+16.5 %; p < 0.0001) and stride length (+6.0 %; p = 0.04) were detected only after DST, while no difference was detected in the CST group. Ankle moment and ROM were unaffected by the training. In PwMS with mild to moderate disability and lower limb dorsiflexors' strength asymmetry, CST was not inferior to DST in inducing significant strength gains in the untrained most-affected limb. However, only DST significantly improved gait performance and, specifically, walking speed. Even though CST did not worsen asymmetry, data suggest that contralateral approaches should not be recommended straightaway if the training goal is to improve outcomes other than strength and, specifically, walking speed.

Sensorized assessment of bilateral hand movements in patients with stroke driven by rhythmic auditory or visual-auditory stimulation.

There is a growing body of literature about the efficacy in neurorehabilitation of the devices providing rhythmic auditory stimulations or visual-auditory stimulations, such as videogames, for guiding the patients' movements. Despite being presented as tools able to motivate patients, their efficacy was not been proven yet, probably due to the limited knowledge about the factors influencing the capability of patients to move the upper limbs following an external stimulus. In this study, we used a marker less system based on two infrared sensors to assess the kinematics of up and down in-phase and anti-phase bilateral hand oscillations synchronized or not with an external stimulus. A group of stroke survivors, one of age-matched healthy subjects and one of young healthy subjects were tested in three conditions: no stimulus, auditory stimulus, and video-auditory stimulus. Our results showed significant negative effects of visual-auditory stimulus in the frequency of movements (p = 0.001), and of auditory stimulus in their fluidity (p = 0.013). These results are conceivably related to the attentional overload required during the execution of bilateral movements driven by an external stimulus. However, a positive effect of external stimulus was found in increasing the range of movements of the less functional hand in all subjects (p = 0.023). These findings highlight as the type of stimulus may play a crucial role in the patient's performance with respect to movements that are not-externally driven.

Accuracy of the Orientation Estimate Obtained Using Four Sensor Fusion Filters Applied to Recordings of Magneto-Inertial Sensors Moving at Three Rotation Rates.

Magneto-Inertial technology is a well-established alternative to optical motion capture for human motion analysis applications since it allows prolonged monitoring in free-living conditions. Magneto and Inertial Measurement Units (MIMUs) integrate a triaxial accelerometer, a triaxial gyroscope and a triaxial magnetometer in a single and lightweight device. The orientation of the body to which a MIMU is attached can be obtained by combining its sensor readings within a sensor fusion framework. Despite several sensor fusion implementations have been proposed, no well-established conclusion about the accuracy level achievable with MIMUs has been reached yet. The aim of this preliminary study was to perform a direct comparison among four popular sensor fusion algorithms applied to the recordings of MIMUs rotating at three different rotation rates, with the orientation provided by a stereophotogrammetric system used as a reference. A procedure for suboptimal determination of the parameter filter values was also proposed. The findings highlighted that all filters exhibited reasonable accuracy (rms errors <; 6.4°). Moreover, in accordance with previous studies, every algorithm's accuracy worsened as the rotation rate increased. At the highest rotation rate, the algorithm from Sabatini (2011) showed the best performance with errors smaller than 4.1° rms.

Inter-leg Distance Measurement as a Tool for Accurate Step Counting in Patients with Multiple Sclerosis.

Step detection is commonly performed using wearable inertial devices. However, methods based on the extraction of signals features may deteriorate their accuracy when applied to very slow walkers with abnormal gait patterns. The aim of this study is to test and validate an innovative step counter method (DiSC) based on the direct measurement of inter-leg distance. Data were recorded using an innovative wearable system which integrates a magneto-inertial unit and multiple distance sensors (DSs) attached to the shank. The method allowed for the detection of both left and right steps using a single device and was validated on thirteen people affected by multiple sclerosis (0 <; EDSS <; 6.5) while performing a six-minute walking test. Two different measurement ranges for the distance sensor were tested (DS200: 0-200 mm; DS400: 0-400 mm). Accuracy was evaluated by comparing the estimates of the DiSC method against video recordings used as gold standard. Preliminary results showed a good accuracy in detecting steps with half the errors in detecting the step of the instrumented side compared to the non-instrumented (mean absolute percentage error 2.4% vs 4.8% for DS200; mean absolute percentage error 2% vs 5.4% for DS400). When averaging errors across patients, over and under estimation errors were compensated, and very high accuracy was achieved (E%<; 1.2% for DS200; E%<; 0.7% for DS400). DS400 is the suggested configuration for patients walking with a large base of support.

In vivo estimation of the shoulder joint center of rotation using magneto-inertial sensors: MRI-based accuracy and repeatability assessment.

BACKGROUND: The human gleno-humeral joint is normally represented as a spherical hinge and its center of rotation is used to construct humerus anatomical axes and as reduction point for the computation of the internal joint moments. The position of the gleno-humeral joint center (GHJC) can be estimated by recording ad hoc shoulder joint movement following a functional approach. In the last years, extensive research has been conducted to improve GHJC estimate as obtained from positioning systems such as stereo-photogrammetry or electromagnetic tracking. Conversely, despite the growing interest for wearable technologies in the field of human movement analysis, no studies investigated the problem of GHJC estimation using miniaturized magneto-inertial measurement units (MIMUs). The aim of this study was to evaluate both accuracy and precision of the GHJC estimation as obtained using a MIMU-based methodology and a functional approach. METHODS: Five different functional methods were implemented and comparatively assessed under different experimental conditions (two types of shoulder motions: cross and star type motion; two joint velocities: ωmax = 90°/s, 180°/s; two ranges of motion: Ɵ = 45°, 90°). Validation was conducted on five healthy subjects and true GHJC locations were obtained using magnetic resonance imaging. RESULTS: The best performing methods (NAP and SAC) showed an accuracy in the estimate of the GHJC between 20.6 and 21.9 mm and repeatability values between 9.4 and 10.4 mm. Methods performance did not show significant differences for the type of arm motion analyzed or a reduction of the arm angular velocity (180°/s and 90°/s). In addition, a reduction of the joint range of motion (90° and 45°) did not seem to influence significantly the GHJC position estimate except in a few subject-method combinations. CONCLUSIONS: MIMU-based functional methods can be used to estimate the GHJC position in vivo with errors of the same order of magnitude than those obtained using traditionally stereo-photogrammetric techniques. The methodology proposed seemed to be robust under different experimental conditions. The present paper was awarded as "SIAMOC Best Methodological Paper 2016".

Estimation of the center of rotation using wearable magneto-inertial sensors.

Determining the center of rotation (CoR) of joints is fundamental to the field of human movement analysis. CoR can be determined using a magneto-inertial measurement unit (MIMU) using a functional approach requiring a calibration exercise. We systematically investigated the influence of different experimental conditions that can affect precision and accuracy while estimating the CoR, such as (a) angular joint velocity, (b) distance between the MIMU and the CoR, (c) type of the joint motion implemented, (d) amplitude of the angular range of motion, (e) model of the MIMU used for data recording, (f) amplitude of additive noise on inertial signals, and (g) amplitude of the errors in the MIMU orientation. The evaluation process was articulated at three levels: assessment through experiments using a mechanical device, mathematical simulation, and an analytical propagation model of the noise. The results reveal that joint angular velocity significantly impacted CoR identification, and hence, slow joint movement should be avoided. An accurate estimation of the MIMU orientation is also fundamental for accurately subtracting the contribution owing to gravity to obtain the coordinate acceleration. The unit should be preferably attached close to the CoR, but both type and range of motion do not appear to be critical. When the proposed methodology is correctly implemented, error in the CoR estimates is expected to be <3mm (best estimates=2±0.5mm). The findings of the present study foster the need to further investigate this methodology for application in human subjects.

Use of a Remote Eye-Tracker for the Analysis of Gaze during Treadmill Walking and Visual Stimuli Exposition.

The knowledge of the visual strategies adopted while walking in cognitively engaging environments is extremely valuable. Analyzing gaze when a treadmill and a virtual reality environment are used as motor rehabilitation tools is therefore critical. Being completely unobtrusive, remote eye-trackers are the most appropriate way to measure the point of gaze. Still, the point of gaze measurements are affected by experimental conditions such as head range of motion and visual stimuli. This study assesses the usability limits and measurement reliability of a remote eye-tracker during treadmill walking while visual stimuli are projected. During treadmill walking, the head remained within the remote eye-tracker workspace. Generally, the quality of the point of gaze measurements declined as the distance from the remote eye-tracker increased and data loss occurred for large gaze angles. The stimulus location (a dot-target) did not influence the point of gaze accuracy, precision, and trackability during both standing and walking. Similar results were obtained when the dot-target was replaced by a static or moving 2D target and "region of interest" analysis was applied. These findings foster the feasibility of the use of a remote eye-tracker for the analysis of gaze during treadmill walking in virtual reality environments.

Foot clearance estimation during overground walking and vertical obstacle passing using shank-mounted MIMUs in healthy and pathological subjects.

A method for assessing maximum foot clearance (maxFCl) during overground walking and obstacle passing using magnetic and inertial measurement units (MIMUs) placed above the malleoli is proposed and validated. The method precision and accuracy were evaluated using a stereo-photogrammetric system as a gold standard. The proposed method was applied to the data obtained from the gait of both healthy subjects and patients with various abnormal gaits. First, an optimally filtered direct and reverse integration (OFDRI) was used for each gait cycle to determine the gait velocity. Then, the effect of an additional OFDRI or a simple DRI approach for obtaining vertical foot displacement was explored. The results showed that the mean absolute errors associated to the maxFCl estimates were about 10% of its range of variation for the healthy and pathological subjects during overground walking. An accurate estimate of the maxFCl during obstacle passing was reached (mean absolute errors less than 5%). Additional testing on gait at various gait speed and on a greater number of subjects should be carried out to fully validate the MIMU-based maxFCl estimates.

Assessment of waveform similarity in clinical gait data: the linear fit method.

The assessment of waveform similarity is a crucial issue in gait analysis for the comparison of kinematic or kinetic patterns with reference data. A typical scenario is in fact the comparison of a patient's gait pattern with a relevant physiological pattern. This study aims to propose and validate a simple method for the assessment of waveform similarity in terms of shape, amplitude, and offset. The method relies on the interpretation of these three parameters, obtained through a linear fit applied to the two data sets under comparison plotted one against the other after time normalization. The validity of this linear fit method was tested in terms of appropriateness (comparing real gait data of 34 patients with cerebrovascular accident with those of 15 healthy subjects), reliability, sensitivity, and specificity (applying a cluster analysis on the real data). Results showed for this method good appropriateness, 94.1% of sensitivity, 93.3% of specificity, and good reliability. The LFM resulted in a simple method suitable for analysing the waveform similarity in clinical gait analysis.

Metrics for describing soft-tissue artefact and its effect on pose, size, and shape of marker clusters.

In human movement analysis based on stereophotogrammetry, bone pose is reconstructed by observing a cluster of skin markers. Each marker undergoes a displacement relative to the underlying bone that is regarded as an artefact (soft-tissue artefact, STA) since it affects accuracy in bone pose estimation. This paper proposes a set of metrics for the statistical description of the STA and its effects on cluster pose, size, and shape, with the intent of contributing to a clearer knowledge of its characteristics, and consequently of setting the bases for the development of more accurate bone pose estimators than presently available. Skin marker clusters behave as deformable bodies in motion relative to the underlying bone. Their motion can be described, based on Procrustes analysis, as the composition of four independent transformations: translation and rotation (rigid motion, RM), and change in size and shape (nonrigid motion, NRM). Statistical parameters describing the time histories of both the individual marker STA and the cluster transformations listed earlier were defined. For demonstration purposes, data collected ex vivo were used. The lower limbs of three cadavers were made to undergo movements with prevailing flexion-extension components. Femur pose was accurately measured using pin markers and the movement of twelve thigh skin markers observed relative to it. The STAs of all possible clusters of four skin markers were analysed. RM and NRM exhibited similar magnitudes and therefore impact on bone pose estimation. Thus bone pose estimators should not account for NRM only, as is normally the case, but also for RM.

Assessment of gait direction changes during straight-ahead walking in healthy elderly and Huntington disease patients using a shank worn MIMU.

The aim of this study was to propose and comparatively evaluate four methods for assessing stride-by-stride changes of direction of progression, during straight walking using measurements of a magnetic and inertial unit placed above the malleolus. The four methods were evaluated by comparing their estimate of the gait changes of direction of progression with that obtained from an instrumented gait mat used as a gold standard. The methods were applied to the data obtained from the gait of both healthy subjects and patients with Huntington Disease, the latter characterized by a jerky swing phase. The results showed that the errors associated to the best estimates of the gait direction changes were about 10% of its range of variability for the healthy subjects and increased to about 30% for the patients, both walking at comfortable speed when the range of variability is the largest. Additional testing on gait at various radius of curvature should be carried out to fully validate the MIMU-based estimates.

Tracking gaze while walking on a treadmill: spatial accuracy and limits of use of a stationary remote eye-tracker.

Inaccurate visual sampling and foot placement may lead to unsafe walking. Virtual environments, challenging obstacle negotiation, may be used to investigate the relationship between the point of gaze and stepping accuracy. A measurement of the point of gaze during walking can be obtained using a remote eye-tracker. The assessment of its performance and limits of applicability is essential to define the areas of interest in a virtual environment and to collect information for the analysis of the visual strategy. The current study aims at characterizing a gaze eye-tracker in static and dynamic conditions. Three different conditions were analyzed: a) looking at a single stimulus during selected head movements b) looking at multiple stimuli distributed on the screen from different distances, c) looking at multiple stimuli distributed on the screen while walking. The eye-tracker was able to measure the point of gaze during the head motion along medio-lateral and vertical directions consistently with the device specifications, while the tracking during the head motion along the anterior-posterior direction resulted to be lower than the device specifications. During head rotation around the vertical direction, the error of the point of gaze was lower than 23 mm. The best accuracy (10 mm) was achieved, consistently to the device specifications, in the static condition performed at 650 mm from the eye-tracker, while point of gaze data were lost while getting closer to the eye-tracker. In general, the accuracy and precision of the point of gaze did not show to be related to the stimulus position. During fast walking (1.1 m/s), the eye-tracker did not lose any data, since the head range of motion was always within the ranges of trackability. The values of accuracy and precision during walking were similar to those resulting from static conditions. These values will be considered in the definition of the size and shape of the areas of interest in the virtual environment.

Design and manufacture of a novel system to simulate the biomechanics of basic and pitching shoulder motion.

OBJECTIVES: Cadaveric models of the shoulder evaluate discrete motion segments using the glenohumeral joint in isolation over a defined trajectory. The aim of this study was to design, manufacture and validate a robotic system to accurately create three-dimensional movement of the upper body and capture it using high-speed motion cameras. METHODS: In particular, we intended to use the robotic system to simulate the normal throwing motion in an intact cadaver. The robotic system consists of a lower frame (to move the torso) and an upper frame (to move an arm) using seven actuators. The actuators accurately reproduced planned trajectories. The marker setup used for motion capture was able to determine the six degrees of freedom of all involved joints during the planned motion of the end effector. RESULTS: The testing system demonstrated high precision and accuracy based on the expected versus observed displacements of individual axes. The maximum coefficient of variation for displacement of unloaded axes was less than 0.5% for all axes. The expected and observed actual displacements had a high level of correlation with coefficients of determination of 1.0 for all axes. CONCLUSIONS: Given that this system can accurately simulate and track simple and complex motion, there is a new opportunity to study kinematics of the shoulder under normal and pathological conditions in a cadaveric shoulder model.

Estimation of stride length in level walking using an inertial measurement unit attached to the foot: a validation of the zero velocity assumption during stance.

In a variety of applications, inertial sensors are used to estimate spatial parameters by double integrating over time their coordinate acceleration components. In human movement applications, the drift inherent to the accelerometer signals is often reduced by exploiting the cyclical nature of gait and under the hypothesis that the velocity of the sensor is zero at some point in stance. In this study, the validity of the latter hypothesis was investigated by determining the minimum velocity of progression of selected points of the foot and shank during the stance phase of the gait cycle while walking at three different speeds on level ground. The errors affecting the accuracy of the stride length estimation resulting from assuming a zero velocity at the beginning of the integration interval were evaluated on twenty healthy subjects. Results showed that the minimum velocity of the selected points on the foot and shank increased as gait speed increased. Whereas the average minimum velocity of the foot locations was lower than 0.011 m/s, the velocity of the shank locations were up to 0.049 m/s corresponding to a percent error of the stride length equal to 3.3%. The preferable foot locations for an inertial sensor resulted to be the calcaneus and the lateral aspect of the rearfoot. In estimating the stride length, the hypothesis that the velocity of the sensor can be set to zero sometimes during stance is acceptable only if the sensor is attached to the foot.