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Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices (WD) and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection (GSD), foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. Methods: Twenty healthy older adults, 20 people with Parkinson’s disease, 20 with multiple sclerosis, 19 with proximal femoral fracture (PFF), 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 hours in the real-world, using a WD worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the WD. We assessed and validated three algorithms for GSD, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. Results: We identified two cohort-specific top performing algorithms for GSD and CAD, and a single best for ICD and SL. GSD best algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (PFF). Algorithms’ performances were lower for short WBs; slower gait speeds (Conclusions: Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findingsshowed that the choice of algorithm for estimation of GSD and CAD DMOs should be cohort-specific (e.g., slow walkers and with gait impairments). Short WB length and slow walking speed worsened algorithms’ performances. Trial registration: ISRCTN – 12246987.

Accurately assessing people’s gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (SDA, including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-hours of real-world unsupervised activity. Excellent absolute agreement (ICC > 0.95) and very limited mean absolute errors were observed for all cohorts and DMOs (cadence ≤ 0.61 steps/min, stride length ≤ 0.02 m, walking speed ≤ 0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the SDA (cadence 2.72–4.87 steps/min, stride length 0.04–0.06 m, walking speed 0.03–0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-hours acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Background: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a multi-task and multi-phase protocol for simulating real-world gait accounting for all these factors within a single set of observations carried out within a limited laboratory space, while ensuring minimisation of participant burden and safety.Methods: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants’ strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohort groups that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson’s Disease (PD), Multiple Sclerosis (MS), Proximal Femoral Fracture (PFF), Chronic Obstructive Pulmonary Disease (COPD) or Congestive Heart Failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks.Results: The protocol proved to be safe and feasible and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a relatively realistic representation of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life.Conclusions: The suitability of the protocol for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy.Trial registration: ISRCTN – 12246987.

Cerebral palsy, the most common childhood neuromotor disorder, is often diagnosed through visual assessment of general movements (GM) in infancy. This skill requires extensive training and is thus difficult to implement on a large scale. Automated analysis of GM performed using low-cost instrumentation in the home may be used to estimate quantitative metrics predictive of movement disorders. This study explored if infants’ GM may be successfully evaluated in a familiar environment by processing the 3D trajectories of points of interest (PoI) obtained from recordings of a single commercial RGB-D sensor. The RGB videos were processed using an open-source markerless motion tracking method which allowed the estimation of the 2D trajectories of the selected PoI and a purposely developed method which allowed the reconstruction of their 3D trajectories making use of the data recorded with the depth sensor. Eight infants’ GM were recorded in the home at 3, 4, and 5 months of age. Eight GM metrics proposed in the literature in addition to a novel metric were estimated from the PoI trajectories at each timepoint. A pediatric neurologist and physiatrist provided an overall clinical evaluation from infants’ video. Subsequently, a comparison between metrics and clinical evaluation was performed. The results demonstrated that GM metrics may be meaningfully estimated and potentially used for early identification of movement disorders.

Contains fulltext : 238527.pdf (Publisher’s version ) (Closed access) BACKGROUND: It is not clear how specific gait measures reflect disease severity across the disease spectrum in Parkinson's disease (PD). OBJECTIVE: To identify the gait and mobility measures that are most sensitive and reflective of PD motor stages and determine the optimal sensor location in each disease stage. METHODS: Cross-sectional wearable-sensor records were collected in 332 patients with PD (Hoehn and Yahr scale I-III) and 100 age-matched healthy controls. Sensors were adhered to the participant's lower back, bilateral ankles, and wrists. Study participants walked in a ~15-meter corridor for 1 minute under two walking conditions: (1) preferred, usual walking speed and (2) walking while engaging in a cognitive task (dual-task). A subgroup (n = 303, 67% PD) also performed the Timed Up and Go test. Multiple machine-learning feature selection and classification algorithms were applied to discriminate between controls and PD and between the different PD severity stages. RESULTS: High discriminatory values were found between motor disease stages with mean sensitivity in the range 72%-83%, specificity 69%-80%, and area under the curve (AUC) 0.76-0.90. Measures from upper-limb sensors best discriminated controls from early PD, turning measures obtained from the trunk sensor were prominent in mid-stage PD, and stride timing and regularity were discriminative in more advanced stages. CONCLUSIONS: Applying machine-learning to multiple, wearable-derived features reveals that different measures of gait and mobility are associated with and discriminate distinct stages of PD. These disparate feature sets can augment the objective monitoring of disease progression and may be useful for cohort selection and power analyses in clinical trials of PD. © 2021 International Parkinson and Movement Disorder Society.

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. This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors’ view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.

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.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).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.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.

Background Physical activity is linked to many positive health outcomes, stimulating the development of exercise programs. However, many falls occur while walking and so promoting activity might paradoxically increase fall rates, causing injuries, and worse quality of life. The relationship between activity exposure and fall rates remains unclear. We investigated the relationship between walking activity (exposure to risk) and fall rates before and after an exercise program (V-TIME). Methods One hundred and nine older fallers, 38 fallers with mild cognitive impairment (MCI), and 128 fallers with Parkinson’s disease (PD) were randomly assigned to one of two active interventions: treadmill training only or treadmill training combined with a virtual reality component. Participants were tested before and after the interventions. Free-living walking activity was characterized by volume, pattern, and variability of ambulatory bouts using an accelerometer positioned on the lower back for 1 week. To evaluate that relationship between fall risk and activity, a normalized index was determined expressing fall rates relative to activity exposure (FRA index), with higher scores indicating a higher risk of falls per steps taken. Results At baseline, the FRA index was higher for fallers with PD compared to those with MCI and older fallers. Walking activity did not change after the intervention for the groups but the FRA index decreased significantly for all groups (p ≤ .035). Conclusions This work showed that V-TIME interventions reduced falls risk without concurrent change in walking activity. We recommend using the FRA index in future fall prevention studies to better understand the nature of intervention programs.

Turning is impaired in people with Parkinson's Disease (PD) and it is a common trigger for freezing of gait (FoG). Recent evidence suggests that people with PD who freeze (PD+FoG) have worse turning performance than those who don't have freezing (non-freezers, PD-FoG), and the freezing episodes are exacerbated by increasing the turn angular amplitude.We investigated the difference between turning 180° while walking versus turning 360° in place, in both single- and dual-task conditions, by means of objective measures in people with PD with and without FoG.Twenty-four PD+FoG and eighteen PD-FoG performed 180° turns while walking and 360° turns in place during single- and dual-task conditions. Quantitative measures of turning and the dual-task cost were computed. Differences were investigated between groups and within turning types using ANOVA. Associations between turn measures and clinical scales were examined with Spearman correlations.Turn duration and the number of steps were greater, and peak angular velocity slower, in PD+FoG compared to PD-FoG (p 0.001). Dual-task costs were similar across groups, but turn duration showed significant interaction (p = 0.03). Posture Instability and Gait Disability (PIGD) subscore was associated with all turn measures in PD-FoG; whereas PIGD was mainly associated with turning while walking in PD+FoG.Objective measures of turning revealed differences between people with and without FoG, specifically, people with FoG showed more impairments in 360° turning in place compared to 180° turning while walking. However, as the turning challenges were increased by adding a dual-task, results from PD+FoG were similar to those from PD-FoG.

The ankle joint complex presents a tangled functional anatomy, which understanding is fundamental to effectively estimate its kinematics on the sagittal plane. Protocols based on the use of magnetic and inertial measurement units (MIMUs) currently do not take in due account this factor. To this aim, a joint coordinate system for the ankle joint complex is proposed, along with a protocol to perform its anatomical calibration using MIMUs, consisting in a combination of anatomical functional calibrations of the tibiotalar axis and static acquisitions. Protocol repeatability and reliability were tested according to the metrics proposed in Schwartz et al. (2004) involving three different operators performing the protocol three times on ten participants, undergoing instrumented gait analysis through both stereophotogrammetry and MIMUs. Instrumental reliability was evaluated comparing the MIMU-derived kinematic traces with the stereophotogrammetric ones, obtained with the same protocol, through the linear fit method. A total of 270 gait cycles were considered. Results showed that the protocol was repeatable and reliable for what concerned the operators (0.4 ± 0.4 deg and 0.8 ± 0.5 deg, respectively). Instrumental reliability analysis showed a mean RMSD of 3.0 ± 1.3 deg, a mean offset of 9.4 ± 8.4 deg and a mean linear relationship strength of R

Stride length is often used to quantitatively evaluate human locomotion performance. Stride by stride estimation can be conveniently obtained from the signals recorded using miniaturized inertial sensors attached to the feet and appropriate algorithms for data fusion and integration. To reduce the detrimental drift effect, different algorithmic solutions can be implemented. However, the overall method accuracy is supposed to depend on the optimal selection of the parameters which are required to be set. This study aimed at evaluating the influence of the main parameters involved in well-established methods for stride length estimation. An optimization process was conducted to improve methods’ performance and preferable values for the considered parameters according to different walking speed ranges are suggested. A parametric solution is also proposed to target the methods on specific subjects’ gait characteristics. The stride length estimates were obtained from straight walking trials of five healthy volunteers and were compared with those obtained from a stereo-photogrammetric system. After parameters tuning, percentage errors for stride length were 1.9%, 2.5% and 2.6% for comfortable, slow, and fast walking conditions, respectively.

Many studies have investigated the bilateral upper limb coordination during movements under different motor and visual conditions. Bilateral training has also been proposed as an effective rehabilitative protocol for patients with stroke. However, the factors influencing in-phase vs. anti-phase coupling have not yet been fully explored. In this study, we used a motion capture device based on two infrared distance sensors to assess whether the up and down oscillation of the less functional hand (the non-dominant one in healthy younger and older subjects and the paretic one in patients with stroke) could be influenced by in-phase or anti-phase coupling of the more functional hand and by visual feedback. Similar patterns were found between single hand movements and in-phase coupled movements, whereas anti-phase coupled movements were less ample, less sinusoidal, but more frequent. These features were particularly evident for patients with stroke who showed a reduced waveform similarity of bilateral movements in all conditions but especially for anti-phase movements under visual control. These results indicate that visuomotor integration in patients with stroke could be less effective than in healthy subjects, probably because of the attentional overload required when moving the two limbs in an alternating fashion.

This work presents a two-dimensional markerless clinical gait analysis protocol to estimate the sagittal lower limb joint kinematics from the markerless recordings of a single RGB-Depth camera. The proposed method includes a subject separation from the background, the definition of a multi-segmental model of the lower limb and the estimation of the relevant joint kinematics. The segmentation algorithm performance was assessed by measuring the similarity between the computer-obtained segmentations and manual tracings (ground-truth). The estimated joint angles were compared to those obtained using a reference optoelectronic marker-based clinical protocol. The offset between the mean waveforms and the RMS value of the waveforms difference after removing their offset were computed. The segmentation accuracy resulted to be higher than 0.92 and very repeatable (STD of JI about 0.01). The RMSD values of the ankle kinematics (3.4° on average) are lower than those of other joints (4.9° for the hip joint and 6.2° for the knee joint, on average). Overall, given the good agreement between our results and those of marker-based method, we propose to use it to develop a new generation of low-cost movement analysis systems.

Contains fulltext : 220639pub.pdf (Publisher’s version ) (Open Access) Contains fulltext : 220639pos.pdf (Author’s version postprint ) (Open Access) Background. People with Parkinson's disease and freezing of gait (FOG+) have more falls, postural instability and cognitive impairment compared with FOG-. Objective. To conduct a secondary analysis of the V-TIME study, a randomized, controlled investigation showing a greater reduction of falls after virtual reality treadmill training (TT + VR) compared with usual treadmill walking (TT) in a mixed population of fallers. We addressed whether these treadmill interventions led to similar gains in FOG+ as in FOG-. Methods. A total of 77 FOG+ and 44 FOG- were assigned randomly to TT + VR or TT. Participants were assessed pre- and posttraining and at 6 months' follow-up. Main outcome was postural stability assessed by the Mini Balance Evaluation System Test (Mini-BEST) test. Falls were documented using diaries. Other outcomes included the New Freezing of Gait Questionnaire (NFOG-Q) and the Trail Making Test (TMT-B). Results. Mini-BEST scores and the TMT-B improved in both groups after training (P = .001), irrespective of study arm and FOG subgroup. However, gains were not retained at 6 months. Both FOG+ and FOG- had a greater reduction of falls after TT + VR compared with TT (P = .008). NFOG-Q scores did not change after both training modes in the FOG+ group. Conclusions. Treadmill walking (with or without VR) improved postural instability in both FOG+ and FOG-, while controlling for disease severity differences. As found previously, TT + VR reduced falls more than TT alone, even among those with FOG. Interestingly, FOG itself was not helped by training, suggesting that although postural instability, falls and FOG are related, they may be controlled by different mechanisms.

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 (0 200 : 0–200 mm; DS 400 : 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 DS 200 ; mean absolute percentage error 2% vs 5.4% for DS 400 ). When averaging errors across patients, over and under estimation errors were compensated, and very high accuracy was achieved (E % 200 ; E % 400 ). DS 400 is the suggested configuration for patients walking with a large base of support.

Magneto-Inertial Measurement Units (MIMUs) are a valid alternative tool to optical stereophotogrammetry in human motion analysis. The orientation of a MIMU may be estimated by using sensor fusion algorithms. Such algorithms require input parameters that are usually set using a trial-and-error (or grid-search ) approach to find the optimal values. However, using trial-and-error requires a known reference orientation, a circumstance rarely occurring in real-life applications. In this article, we present a way to suboptimally set input parameters, by exploiting the assumption that two MIMUs rigidly connected are expected to show no orientation difference during motion. This approach was validated by applying it to the popular complementary filter by Madgwick et al. and tested on 18 experimental conditions including three commercial products, three angular rates, and two dimensionality motion conditions. Two main findings were observed: i) the selection of the optimal parameter value strongly depends on the specific experimental conditions considered, ii) in 15 out of 18 conditions the errors obtained using the proposed approach and the trial-and-error were coincident, while in the other cases the maximum discrepancy amounted to 2.5 deg and less than 1.5 deg on average. This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors’ view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein., {"references":["Caruso, M., Sabatini, A. M., Knaflitz, M., Gazzoni M., Croce, U. D., Cereatti, A. (2020). Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning. IEEE Sensors Journal, 21(3), 3408-3419."]}

Magnetic and inertial measurement units (MIMUs) may provide an accessible, three-dimensional, in-field alternative to laboratory-restricted marker-based motion capture. Existing upper limb MIMU models have predominantly been validated with low-velocity motion and their suitability for use with sport-based movements remains relatively untested. We propose a MIMU system approach to enable the estimation of anatomically meaningful and participant-specific elbow kinematics with considerations for use with cricket bowling. A novel standardised elbow reference posture of 90 degrees flexion and 0 deg pronation, and functional definition of elbow joint axes of rotation calibrated the MIMU method model before it was validated across three experiments: (1) simple elbow rotations with a mechanical linkage; (2) low-velocity elbow rotations in human participants; and (3) low-medium velocity sport-based movements in human participants. The proposed MIMU method demonstrated high elbow kinematic measurement agreement when compared with a criterion measure across all three conditions. However, during experiment 3, sensor components neared their measurement capacity and the MIMU method elbow flexion measurement variability increased. We conclude that the proposed MIMU method can estimate anatomically referenced, participant-specific joint angles, however, the hardware specifications of currently available systems may limit application in high-velocity/acceleration situations, preventing the measurement of cricket bowling in-field for now.

The International Society of Biomechanics (ISB) has charged this committee with development of a standard similar in scope to the kinematic standard proposed in Wu et al. (2002) and Wu et al. (2005). Given the variety of purposes for which intersegmental forces and moments are used in biomechanical research, it is not possible to recommend a particular set of analysis standards that will be acceptable in all applications. Instead, it is the purpose of this paper to recommend a set of reporting standards that will result in an understanding of the differences between investigations and the ability to reproduce the research. The end products of this standard are (1) a critical checklist that can be used during submission of manuscripts and abstracts to insure adequate description of methods, and (2) a web based visualization tool that can be used to alter the coordinate system, normalization technique and internal/external perspective of intersegmental forces and moments during walking and running so that the shape and magnitude of the curves can be compared to one's own data.

The estimate of a consistent and clinically meaningful joint kinematics using wearable inertial and magnetic sensors requires a sensor-to-segment coordinate system calibration. State-of-the-art calibration procedures for the upper limb are based on functional movements and/or pre-determined postures, which are difficult to implement in subjects that have impaired mobility or are bedridden in acute units. The aim of this study was to develop and validate an alternative calibration procedure based on the direct identification of palpable anatomical landmarks (ALs) for an inertial and magnetic sensor-based upper limb movement analysis protocol. The proposed calibration procedure provides an estimate of three-dimensional shoulder/elbow angular kinematics and the linear trajectory of the wrist according to the standards proposed by the International Society of Biomechanics. The validity of the method was assessed against a camera-based optoelectronic system during uniaxial joint rotations and a reach-to-grasp task. Joint angular kinematics was found as characterised by a low-biased range of motion (2 > 0.995) with respect to the gold standard. Except for the cranio–caudal direction, the linear trajectory of the wrist was characterised by a low-biased range of motion (2 > 0.968). The proposed method enabled the estimation of reliable joint kinematics without requiring any active involvement of the patient during the calibration procedure, complying with the metrological standards and requirements of clinical movement analysis.

Among different exercise models proposed for individuals with Parkinson's disease (IwPD), the popularity of traditional forms of dance is increasing. The aim of this study was to evaluate the effects of Sardinian folk dance (Ballu Sardu, BS) on functional performance and motor and nonmotor symptoms in IwPD.Single-blind, randomized controlled pilot trial.Outpatient health clinic.Twenty IwPD (13M, 7F; 67.4 ± 6.1 years) were randomly assigned to BS (n = 10) or usual care (n = 10). The dance program consisted of two sessions/week, 90-min/class, for 12 weeks.Motor and nonmotor symptoms, as well as functional performance, were evaluated using different questionnaires and tests such as the Unified Parkinson's Disease Rating Scale Part-III (UPDRS-III), 6-min walking test (6MWT), Berg Balance Scale (BBS), Timed Up-and-Go (TUG) test, Five Times Sit-to-Stand Test (FTSST), Back Scratch Test (BST), Sit-and-Reach Test (SRT), instrumented gait analysis, Parkinson's Disease Fatigue Scale (PFS-16), Beck Depression Inventory, Starkstein Apathy Scale (SAS), and Montreal Cognitive Assessment (MOCA) scale.Repeated-measures analysis of variance revealed significant Time × Group interactions for UPDRS-III and functional variables such as the 6MWT, BBS, FTSST, TUG (all, p 0.001), BST (p = 0.04), and gait analysis parameters (stride length, p = 0.031; gait speed, p = 0.049; and gait fatigue index (GFI), p = 0.005). For nonmotor symptoms, significant Time × Group interactions for depression (p 0.001), apathy (p = 0.016), and MOCA scores (p = 0.012) were observed. Of note, for GFI and SAS, the BS group only showed a trend toward improvement, while the condition of the controls worsened significantly. No between-group differences were observed for SRT and PFS-16.BS is an enjoyable activity, which has been proved to be superior to usual care alone in inducing changes in different motor and nonmotor symptoms associated with PD. Results show that BS can be considered a safe tool for contrasting impairments observed in IwPD due to the intrinsic nature of the neurodegenerative disease.

We compared in-lab usual-walking (UW) and dual-task walking (DTW) to daily-living measures of gait obtained during 24/7 monitoring. In-lab gait features (e.g., gait speed, step and stride regularity) derived from UW and DTW were compared to the same gait features during daily-living in 150 elderly fallers (age: 76.5±6.3 years, 37.6% men). Features were extracted from a lower-back accelerometer. In daily-living setting, subjects wore the device for one week and pre-processing detected 30-second walking bouts. A histogram of all walking bouts was determined for each walking feature for each subject, then each subject’s typical, worst and best values were determined. Statistics of reliability were assessed using ICC and Bland-Altman. As expected, in-lab gait speed, step regularity, and stride regularity were worse during DTW, compared to UW. Gait speed, step regularity, and stride regularity during UW were significantly higher (i.e., better) from the typical daily-living values (p

Background: The use of miniaturized magneto-inertial measurement units (MIMUs) allows for an objective evaluation of gait and a quantitative assessment of clinical outcomes. Spatial and temporal parameters are generally recognized as key metrics for characterizing gait. Although several methods for their estimate have been proposed, a thorough error analysis across different pathologies, multiple clinical centers and on large sample size is still missing. The aim of this study was to apply a previously presented method for the estimate of spatio-temporal parameters, named Trusted Events and Acceleration Direct and Reverse Integration along the direction of Progression (TEADRIP), on a large cohort (236 patients) including Parkinson, mildly cognitively impaired and healthy older adults collected in four clinical centers. Data were collected during straight-line gait, at normal and fast walking speed, by attaching two MIMUs just above the ankles. The parameters stride, step, stance and swing durations, as well as stride length and gait velocity, were estimated for each gait cycle. The TEADRIP performance was validated against data from an instrumented mat.Results: Limits of agreements computed between the TEADRIP estimates and the reference values from the instrumented mat were − 27 to 27 ms for Stride Time, − 68 to 44 ms for Stance Time, − 31 to 31 ms for Step Time and − 67 to 52 mm for Stride Length. For each clinical center, the mean absolute errors averaged across subjects for the estimation of temporal parameters ranged between 1 and 4%, being on average less than 3% (Conclusions: The TEADRIP method was effectively validated on a large number of healthy and pathological subjects recorded in four different clinical centers. Results showed that the spatio-temporal parameters estimation errors were consistent with those previously found on smaller population samples in a single center. The combination of robustness and range of applicability suggests the use of the TEADRIP as a suitable MIMU-based method for gait spatio-temporal parameter estimate in the routine clinical use. The present paper was awarded the "SIAMOC Best Methodological Paper 2017".

Inertial sensor technology has assumed an increasingly important role in the field of human motion analysis. However, the reliability of the kinematic estimates could still be critical for specific applications in the field of functional evaluation and motor rehabilitation. Within this context, the definition of subject-specific multi-body kinematic models is crucial since it affects the accuracy and repeatability of movement reconstruction. A key step for kinematic model calibration is the determination of bony segment lengths. This study proposes a functional approach for the in vivo estimation of the humerus length using a single magneto-inertial measurement unit (MIMU) positioned on the right distal posterior forearm. The humerus length was estimated as the distance between the shoulder elevation axis and the elbow flexion–extension axis. The calibration exercise involved five shoulder elevations in the sagittal plane with the elbow completely extended and five elbow flexion–extensions with the upper arm rigidly aligned to the trunk. Validation of the method was conducted on five healthy subjects using the humerus length computed from magnetic resonance imaging as the gold standard. The method showed mean absolute errors of 12 ± 9 mm, which were in the estimate of the humerus length. When using magneto-inertial technology, the proposed functional method represents a promising alternative to the regressive methods or manual measurements for performing kinematic model calibrations. Although the proposed methodology was validated for the estimation of the humerus length, the same approach can be potentially extended to other body segments.

Accurate estimation of the position and orientation (pose) of a bone from a cluster of skin markers is limited mostly by the relative motion between the bone and the markers, which is known as the Soft Tissue Artifact (STA). This work presents a method, based on continuum mechanics, to describe the kinematics of a cluster affected by STA. The cluster is characterized by Triangular Cosserat Point Elements (TCPEs) defined by all combinations of three markers. The effects of the STA on the TCPEs are quantified using three parameters describing the strain in each TCPE and the relative rotation and translation between TCPEs. The method was evaluated using previously collected ex-vivo kinematic data. Femur pose was estimated from 12 skin markers on the thigh, while its reference pose was measured using bone pins. Analysis revealed that instantaneous subsets of TCPEs exist which estimate bone position and orientation more accurately than the Procrustes Superimposition applied to the cluster of all markers. It has been shown that some of these parameters correlate well with femur pose errors, which suggests that they can be used to select, at each instant, subsets of TCPEs leading an improved estimation of the underlying bone pose.

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”.

Bio-imaging techniques represent a powerful tool for shoulder joint biomechanical analysis. However, the restricted field of view may prevent the acquisition of complete scapula and humerus bone models and hence limiting the applicability of standardized anatomical coordinate system (ACS) definitions. The aim of this study was to propose ACS definitions for both scapula and humerus which can be implemented when limited portions of the relevant bones are available. Magnetic resonance (MR) images of twenty right humeri and scapulae were acquired. The proposed ACSs were assessed in terms of (1) sensitivity to bone morphological variation, (2) intra – and inter – operator repeatability and (3) consistency with the anatomical cardinal directions. A comparison with alternative ACS definitions was also performed. Overall, our ACS scapular proposal and that presented in Kedgley and Dunning (2010) were found to be the least sensitive to the morphometric variability (mean angular absolute deviation lower than 8.3 deg) and they were characterized by a high intra – and inter – operator repeatability (mean angular absolute deviation lower than 1.5 deg). The humeral ACS proposal showed a morphometric variability similar to Amadi et al. (2009b) (mean angular absolute deviation lower than 8.3 deg) but a higher reproducibility. The scapular and humeral ACS mean angular deviation from the reference anatomical cardinal directions were smaller than 15 deg and 8.6 deg, respectively. The proposed scapular and humeral ACS definitions are therefore suitable to be applied when a limited portion of the glenohumeral joint is available as it may occur in standard shoulder clinical exams.

Background The description of the three-dimensional (3D) trajectory of the body center of mass (BCoM) provides useful insights on the mechanics of locomotion. The BCoM trajectory can be estimated from ground reaction forces, recorded by force platforms (GRF, gold standard), or from marker trajectories recorded by stereophotogrammetric systems (MKR). However, both instruments do not allow for monitoring locomotion in the real-life environment. In this perspective, magneto-inertial measurement units (MIMUs) are particularly attractive being wearable, thus enabling to collect movement data out of the laboratory. Research questions To investigate the feasibility and accuracy of a recent marketed full-body MIMU-based method for the estimation of the 3D BCoM trajectory and energetics during walking. Methods Twelve subjects walked at self-selected and slow speed along a 12 m long walkway. GRF and MKR were acquired using three force platforms and a stereophotogrammetric system. MIMU data were collected using a full-body MIMU-based motion capture system (Xsens MTw Awinda). The 3D BCoM trajectory, external mechanical work and energy recovery were extracted from the data acquired by the three measurement systems, using state-of-the-art methods. The accuracy of both MKR- and MIMU-based estimates compared with GRF was assessed for the BCoM trajectory (maximum, minimum, range, and RMSD), as well as for mechanical work and energy recovery. Results A total number of 108 strides were analyzed. MIMU-based BCoM trajectory displayed larger errors in comparison with GRF (and MKR) for the trajectory ranges: 89 ± 47(93 ± 44)% in antero-posterior, 46 ± 25(40 ± 79)% medio-lateral and -13 ± 23(-5 ± 25)% vertical directions, leading to a 3D RMSD of 17 ± 5(12 ± 5) mm (mean ± SD). These discrepancies largely affected the estimation of both mechanical work and energy recovery (+115 ± 85% and -28 ± 21%, respectively). Significance Preliminary findings highlighted that the tested MIMU-based method for BCoM trajectory estimation still lacks accuracy and that the quantification of energetics in real-life situations remains an open challenge.

Hypothesis: In this study, we aim to test whether scapular winging results in a significant change in glenohumeral translation in the initial phase of the throwing motion. Methods: Six shoulders underwent an abbreviated throwing motion (ATM) from late cocking to the end of acceleration by use of a validated robotic system. The intact specimens were tested to establish a baseline. The position of the scapula was then affected to simulate scapular winging by placing a cylindrical wedge under the inferior angle of the scapula, and the ATM was performed again. For both conditions, the average glenohumeral translations and scapular rotations were plotted over time to calculate the area under the curve, as a representative of the overall glenohumeral translations and scapular rotations observed during the ATM. Results: Throughout the motion, the winged scapulae showed, on average, 7.7 � more upward rotation, 1.6 � more internal rotation, and 5.3 � more anterior tipping as compared with the baseline. The scapular position relative to the hanging arm was significantly different between the baseline and scapular winging conditions in all arm positions, except for maximal external rotation and the neutral position. Comparing the area under the curve at baseline and with scapular winging indicated that scapular winging significantly increased anterior translation of the glenohumeral joint whereas translation in the superior/inferior and medial/lateral directions did not result in a change in translation. Discussion: These results may suggest a more important role of abnormalities in scapular position in predisposing throwing athletes to shoulder injuries of the anterior capsulolabral structures and consecutive glenohumeral instability. Level of evidence: Basic Science Study, Biomechanics. 2013 Journal of Shoulder and Elbow Surgery Board of Trustees.

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

Bluetooth Low Energy (BLE) is a wireless technology for exchanging data, over short distances, designed for the Internet-of-Things era. As widely supported by wearable devices, BLE has the potential to become an alternative for indoor-localization and proximity sensing. The aim of this work was to perform a thorough characterization of the RSSI-distance relationship under controlled conditions using two BLE devices. Four calibration models underwent to a comparative evaluation analysis. The best results were obtained using a polynomial model with a mean distance percentage error equal to 25.7% (0.4 m) in the range 0–3 m. An overall improvement of 14.3% (0.24 m) in the distance estimate compared to the exponential model commonly adopted in the literature was reported.

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.

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.

Despite the widespread use of Magnetic and Inertial Measurement Units (MIMUs) for movement reconstruction, only a few studies have tackled issues related to their accuracy. It has been proved that their performance decreases over a period of use since calibration parameters become no longer effective. Good practice rules recommend to assess, prior to any experimental session, the instrumental errors associated to the relevant measures. Aim of this study was to provide a practical and reproducible spot check for assessing the performance of MIMUs in terms of consistency in determining their orientation with respect to a common (inter-MIMUs consistency, IC) and invariant (self-MIMU consistency, SC) global frame. IC was assessed by verifying the hypothesis that the orientation of 9 MIMUs aligned to each other on a rigid Plexiglas plank coincided at any orientation of the plank. SC was assessed separately by verifying differences between measured and imposed known rotations imparted to each MIMU. The orientation of MIMUs relative to the global frame was expressed in terms of quaternion. IC test showed that MIMUs defined their orientation differently. This difference was not constant but varied according to the plank's orientation. The least consistent MIMU showed discrepancy up to 5.7°. SC test confirmed the same MIMU as that affected by the highest inaccuracy (8.4°), whereas it revealed errors within limits (1°) in correspondence to other MIMUs. A tool has been proposed that allows the users to be aware of the errors that may be expected when using MIMUs for the estimate of absolute and relative segments kinematics.

To estimate hip joint angles during selected motor tasks using stereophotogrammetric data, it is necessary to determine the hip joint centre position. The question is whether the errors affecting that determination propagate less to the angles estimates when a three degrees of freedom (DOFs) constraint (spherical hinge) is used between femur and pelvis, rather than when the two bones are assumed to be unconstrained (six DOFs). An analytical relationship between the hip joint centre location error and the joint angle error was obtained limited to the planar case. In the 3-D case, a similar relationship was obtained using a simulation approach based on experimental data. The joint angle patterns resulted in a larger distortion using a constrained approach, especially when wider rotations occur. The range of motion of the hip flexion-extension, obtained simulating different location errors and without taking into account soft tissue artefacts, varied approximately 7 deg using a constrained approach and up to 1 deg when calculated with an unconstrained approach. Thus, the unconstrained approach should be preferred even though its estimated three linear DOFs most unlikely carry meaningful information.

The estimation of gait temporal parameters with inertial measurement units (IMU) is a research topic of interest in clinical gait analysis. Several methods, based on the use of a single IMU mounted at waist level, have been proposed for the estimate of these parameters showing satisfactory performance when applied to the gait of healthy subjects. However, the above mentioned methods were developed and validated on healthy subjects and their applicability in pathological gait conditions was not systematically explored. We tested the three best performing methods found in a previous comparative study on data acquired from 10 older adults, 10 hemiparetic, 10 Parkinson's disease and 10 Huntington's disease subjects. An instrumented gait mat was used as gold standard. When pathological populations were analyzed, missed or extra events were found for all methods and a global decrease of their performance was observed to different extents depending on the specific group analyzed. The results revealed that none of the tested methods outperformed the others in terms of accuracy of the gait parameters determination for all the populations except the Parkinson's disease subjects group for which one of the methods performed better than others. The hemiparetic subjects group was the most critical group to analyze (stride duration errors between 4-5 % and step duration errors between 8-13 % of the actual values across methods). Only one method provides estimates of the stance and swing durations which however should be interpreted with caution in pathological populations (stance duration errors between 6-14 %, swing duration errors between 10-32 % of the actual values across populations).

Gait and cognitive deficits are common in multiple sclerosis (MS) and are negatively affected during dual-task walking. Treadmill (TM) training has been previously used to preserve locomotor activity in MS. Virtual reality (VR) engages the user in cognitive and motor activities simultaneously. A training combining TM and VR has been successfully adopted in several neurological diseases, but not in MS. This study aims at investigating the feasibility of a VR-based TM training program on gait of subjects with MS. Eight persons with relapsing-remitting MS were recruited to participate in a six-week VR-based TM training program. Gait analysis was performed both in single and dual task conditions. Clinical tests were used to assess walking endurance and obstacle negotiation. All the evaluations were performed before, immediately and one month after the training. Gait speed and stride length improved in dual task post-intervention and were retained at follow-up. An improved ability in negotiating obstacles was found across the evaluations. VR-based TM training program is feasible and safe for MS subjects with moderate disabilities and may positively affect gait under complex conditions, such as dual tasking and obstacle negotiation.

The location of the centre of rotation of human joints that can be modelled as a spherical hinge can be estimated using kinematics information about the two adjacent bony segments involved recorded while the subject makes them move one relative to the other (functional method). In order to solve the relevant analytical problem, several algorithms have been proposed. Most recently, two methods, one based on a spherical best-fit approach and another based on the Reuleaux construction, have been presented as being different and submitted to comparative evaluation. This paper modifies the second method taking all information in the data set into account and shows that, having done this, the two methods coincide analytically.