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Background: Patients with age-related white matter changes (ARWMC) frequently present a gait disorder, depression and cognitive impairment. Our aims are to define which alterations in the gait parameters are associated with motor or neuro-psychological impairment and to assess the role of motor, mood or cognitive dysfunction in explaining the variance of the gait parameters. Methods: Patients with gait disorders admitted to a Neuro-rehabilitation Department, affected by vascular leukoencephalopathy who had ARWMC confirmed by a brain MRI, were consecutively enrolled, classified by a neuroradiological scale (Fazekas 1987) and compared to healthy controls. We excluded subjects unable to walk independently, subjects with hydrocephalus or severe aphasia, with orthopaedic and other neurological pathologies conditioning the walking pattern. Patients and controls were assessed by clinical and functional scales (Mini Mental State Examination, Geriatric Depression Scale, Nevitt Motor Performance Scale, Berg Balance Scale, Functional Independence Measure), and computerised gait analysis was performed to assess the spatial and temporal gait parameters in a cross-sectional study. Results: We recruited 76 patients (48 males, aged 78.3 ± 6.2 years) and 14 controls (6 males, aged 75.8 ± 5 years). In the multiple regression analysis, the gait parameter with overall best model summary values, associated with the ARWMC severity, was the stride length even after correction for age, sex, weight and height (R2 = 0.327). The motor performances justified at least in part of the gait disorder (R2 change = 0.220), but the mood state accounted independently for gait alterations (R2 change = 0.039). The increase in ARWMC severity, the reduction of motor performance and a depressed mood state were associated with a reduction of stride length (R = 0.766, R2 = 0.587), reduction of gait speed (R2 = 0.573) and an increase in double support time (R2 = 0.421). Conclusion: The gait disorders in patients with ARWMC are related to motor impairment, but the presence of depression is an independent factor for determining gait alterations and functional status. These data pave the way for longitudinal studies, including gait parameters, to quantitatively assess gait changes after treatment or to monitor the natural progression of the gait disorders.

The aim of this study was to determine a gait pattern, i.e., a subset of spatial and temporal parameters, through a supervised machine learning (ML) approach, which could be used to reliably distinguish Parkinson’s Disease (PD) patients with and without mild cognitive impairment (MCI). Thus, 80 PD patients underwent gait analysis and spatial–temporal parameters were acquired in three different conditions (normal gait, motor dual task and cognitive dual task). Statistical analysis was performed to investigate the data and, then, five ML algorithms and the wrapper method were implemented: Decision Tree (DT), Random Forest (RF), Naïve Bayes (NB), Support Vector Machine (SVM) and K-Nearest Neighbour (KNN). First, the algorithms for classifying PD patients with MCI were trained and validated on an internal dataset (sixty patients) and, then, the performance was tested by using an external dataset (twenty patients). Specificity, sensitivity, precision, accuracy and area under the receiver operating characteristic curve were calculated. SVM and RF showed the best performance and detected MCI with an accuracy of over 80.0%. The key features emerging from this study are stance phase, mean velocity, step length and cycle length; moreover, the major number of features selected by the wrapper belonged to the cognitive dual task, thus, supporting the close relationship between gait dysfunction and MCI in PD.

Drop foot is a syndrome characterised by the difficulty in lifting the front part of the foot, caused by the weakness or disability of muscles responsible for foot dorsiflexion. Ankle Foot Orthosis (AFO) is an orthopaedic support used in drop foot patients to support and maintain the foot and ankle in the proper position during movement, improving the gait pattern. In this study we investigated the effect and clinical relevance of the use of an AFO on walking ability in patients suffering drop foot syndrome. Two Machine Learning (ML) algorithms were implemented on Knime Analytic Platform: Decision Tree (DT) and Random Forest (RF). They were used on a set of spatio-temporal gait variables assessed by means of the IMU-based wearable system for gait analysis, namely Opal Mobility Lab by APDM, on 19 patients with unilateral drop foot syndrome, in two separate conditions: wearing or not the AFO. The following evaluation metrics were used to evaluate the performances of the two tree-based ML models: Recall, Precision, Sensitivity, Specificity, F-measure, Accuracy and Area under the Receiver Operating Characteristic Curve (AucRoc). Moreover a Feature Importance analysis was carried out. Results demonstrate RF was perfect in distinguishing the two classes - walking with and without AFO - while DT achieved a slightly lower classification score but still of high discriminative power, confirming the effective incidence of the use of the AFO on walking pattern. The following parameters were identified as the most informative by the Feature Importance analysis: stance and swing phase duration, cadence, step duration and stride length.

Background: Total knee arthroplasty (TKA) is a common and cost-effective surgical treatment for osteoarthritis of the knee. However, only 82-89% of patients who performed TKA are satisfied with the postoperative outcomes. Therefore, bi-cruciate retaining (BCR) TKA is re-attracting attention. By retaining the anterior cruciate ligament (ACL), the knee may obtain the kinematic pathway that are closer to the native knee. The aim of the present study is to compare the ability to walk before and after surgery in patients who underwent bi-cruciate retaining total knee arthroplasty (BCR TKA) versus bi-cruciate stabilized (BCS) TKA during the early postoperative period. Methods: Subjects included patients who underwent BCR TKA (10 knees) and BCS TKA (15 knees). We administered 10-meter gait tests before surgery and at 6 weeks and 3 months after surgery. We collected the following triaxial accelerometery data with a portable gait analyzer: walking time, number of steps, velocity, stride length, and coefficient of variability (CV) of double-leg support time while walking. Results: Patients who underwent BCR TKA improved their gait ability [walking time (p < 0.01), number of steps (p < 0.05), velocity (p < 0.01), and stride length (p < 0.01) more than those who received BCS TKA at 6 weeks after surgery. BCR TKA improved gait ability (walking time, number of steps, velocity, and stride length) more than BCS TKA at 6 weeks after surgery. At 6 weeks after surgery, CV of double-leg support time while walking improved more in the BCR TKA group than in the BCS TKA group (p < 0.05). Conclusions: BCR TKA is associated with improved gait ability in the early postoperative period.

With the goal to restore ankle and foot function also in the long term, custom-made prostheses are becoming more frequently possible solutions for severe bone loss and avascular necrosis of the talus. A young professional rock climber was implanted with a custom-made talonavicular prosthesis, and short-term (30 months) assessment has been published. A thorough assessment at the intermediate term (60 months), with state-of-the-art gait and medical imaging analyses, is reported here. Level walking and more demanding motor tasks were analyzed with both a full-body and a multisegment foot protocol on the operated and contralateral limbs. Cone-beam computer-tomography was also used to obtain 3-dimensional (3D) position and orientation of bone models on the operated ankle. These models were also used for a 3D video fluoroscopy analysis, with the ankle in 3 joint positions at the extremes of motion. Distance map analysis was performed to check for possible changes over time of bone morphology and joint contact areas, in all 3 joint positions. Very satisfactory functional results were observed, with large and symmetric joint motion and physiological muscular recruitment even in demanding motor tasks. Distance map analyses revealed that very small morphologic and contact patterns changes occurred in the replaced ankle between 30 and 60 months. Concerns about possible wear of the cartilage in the tibial mortise are not yet supported by experimental evidence.

Dravet syndrome (DS) is a rare and severe form of genetic epilepsy characterized by cognitive and behavioural impairments and progressive gait deterioration. The characterization of gait parameters in DS needs efficient, non-invasive quantification. The aim of the present study is to apply nonlinear indexes calculated from inertial measurements to describe the dynamics of DS gait. Twenty participants (7 M, age 9–33 years) diagnosed with DS were enrolled. Three wearable inertial measurement units (OPAL, Apdm, Portland, OR, USA; Miniwave, Cometa s.r.l., Italy) were attached to the lower back and ankles and 3D acceleration and angular velocity were acquired while participants walked back and forth along a straight path. Segmental kinematics were acquired by means of stereophotogrammetry (SMART, BTS). Community functioning data were collected using the functional independence measure (FIM). Mean velocity and step width were calculated from stereophotogrammetric data; fundamental frequency, harmonic ratio, recurrence quantification analysis, and multiscale entropy (τ = 1...6) indexes along anteroposterior (AP), mediolateral (ML), and vertical (V) axes were calculated from trunk acceleration. Results were compared to a reference age-matched control group (112 subjects, 6–25 years old). All nonlinear indexes show a disruption of the cyclic pattern of the centre of mass in the sagittal plane, quantitatively supporting the clinical observation of ataxic gait. Indexes in the ML direction were less altered, suggesting the efficacy of the compensatory strategy (widening the base of support). Nonlinear indexes correlated significantly with functional scores (i.e., FIM and speed), confirming their effectiveness in capturing clinically meaningful biomarkers of gait.

There is growing interest in the quantification of gait as part of complex motor tasks. This requires gait events (GEs) to be detected under conditions different from straight walking. This study aimed to propose and validate a new marker-based GE detection method, which is also suitable for curvilinear walking and step negotiation. The method was first tested against existing algorithms using data from healthy young adults (YA, n = 20) and then assessed in data from 10 individuals from the following five cohorts: older adults, chronic obstructive pulmonary disease, multiple sclerosis, Parkinson’s disease, and proximal femur fracture. The propagation of the errors associated with GE detection on the calculation of stride length, duration, speed, and stance/swing durations was investigated. All participants performed a variety of motor tasks including curvilinear walking and step negotiation, while reference GEs were identified using a validated methodology exploiting pressure insole signals. Sensitivity, positive predictive values (PPV), F1-score, bias, precision, and accuracy were calculated. Absolute agreement [intraclass correlation coefficient (ICC2,1)] between marker-based and pressure insole stride parameters was also tested. In the YA cohort, the proposed method outperformed the existing ones, with sensitivity, PPV, and F1 scores ≥ 99% for both GEs and conditions, with a virtually null bias (ICC2,1=0.817− 0.999). In conclusion, the proposed method accurately detects GE from marker data under different walking conditions and for a variety of gait impairments.

BackgroundMild cognitive impairment (MCI) is frequent in Parkinson’s disease (PD) and represents a risk factor for the development of dementia associated with PD (PDD). Since PDD has been associated with disability, caregiver burden, and an increase in health-related costs, early detection of MCI associated with PD (PD-MCI) and its biomarkers is crucial.ObjectiveGiven that gait is considered a surrogate marker for cognitive decline in PD, the aim of this study was to compare gait patterns in PD-MCI subtypes in order to verify the existence of an association between specific gait features and particular MCI subtypes.MethodsA total of 67 patients with PD were consecutively enrolled and assessed by an extensive clinical and cognitive examination. Based on the neuropsychological examination, patients were diagnosed as patients with MCI (PD-MCI) and without MCI (no-PD-MCI) and categorized in MCI subtypes. All patients were evaluated using a motion capture system of a BTS Bioengineering equipped with six IR digital cameras. Gait of the patients was assessed in the ON-state under three different tasks (a single task and two dual tasks). Statistical analysis included the t-test, the Kruskal–Wallis test with post hoc analysis, and the exploratory correlation analysis.ResultsGait pattern was poorer in PD-MCI vs. no-PD-MCI in all tasks. Among PD-MCI subtypes, multiple-domain PD-MCI and amnestic PD-MCI were coupled with worse gait patterns, notably in the dual task.ConclusionBoth the magnitude of cognitive impairment and the presence of memory dysfunction are associated with increased measures of dynamic unbalance, especially in dual-task conditions, likely mirroring the progressive involvement of posterior cortical networks.

Torsional deformities of the lower limb are common in children with cerebral palsy (CP)-determining gait problems. The mechanisms underlying transverse plane gait deviations arise from a combination of dynamic and static factors. The dynamic elements may be due to spasticity, contractures and muscle imbalances, while the static ones may result from excessive femoral anteversion, which decreases the efficiency of the hip abductors by reducing the muscular lever arms. A therapeutic approach has been identified in multi-level functional surgery for the lower limb. Treating the malalignments of the lower limb with femoral or tibial derotation provides optimal results, especially when supported by adequate biomechanical planning. This planning requires an integrated static-dynamic approach of morphological and functional evaluation, based on radiological measurements, physical examination and gait analysis. Instrumented gait analysis has been confirmed as essential in the evaluation and surgical decision making process for children affected by CP with transverse plane deformities. Computational simulations based on musculoskeletal models that integrate patient-specific CT morphological data into gait analysis can be used for the implementation of a surgical simulation system in pre-operative planning to test the possible effects of the different surgical treatment options on the torsional defects of the lower limbs. Recently, a computer-aided simulation process has been implemented in the preoperative planning of complex osteotomies for limb deformities in children. Three-dimensional (3D) digital models were generated from Computed Tomography (CT) scans, using free open-source software. The aim of this study is to integrate the patient-specific CT musculoskeletal model with morphological data and gait analysis data, with the personalized calculation of kinematic and kinetic parameters, which allow us to generate an “avatar” of the patient for a more in-depth evaluation of the gait abnormalities. The computational simulation platform proposed provides a realistic movable musculoskeletal model in a virtual environment, with the possibility of planning and monitoring the effects of virtual three-dimensional surgical corrections.

BackgroundClinical markers of cognitive decline in Parkinson's disease (PD) encompass several mental non-motor symptoms such as hallucinations, apathy, anxiety, and depression. Furthermore, freezing of gait (FOG) and specific gait alterations have been associated with cognitive dysfunction in PD. Finally, although low cerebrospinal fluid levels of amyloid-β42 have been found to predict cognitive decline in PD, hitherto PET imaging of amyloid-β (Aβ) failed to consistently demonstrate the association between Aβ plaques deposition and mild cognitive impairment in PD (PD-MCI).AimFinding significant features associated with PD-MCI through a machine learning approach.Patients and methodsPatients were assessed with an extensive clinical and neuropsychological examination. Clinical evaluation included the assessment of mental non-motor symptoms and FOG using the specific items of the MDS-UPDRS I and II. Based on the neuropsychological examination, patients were classified as subjects without and with MCI (noPD-MCI, PD-MCI). All patients were evaluated using a motion analysis system. A subgroup of PD patients also underwent amyloid PET imaging. PD-MCI and noPD-MCI subjects were compared with a univariate statistical analysis on demographic data, clinical features, gait analysis variables, and amyloid PET data. Then, machine learning analysis was performed two times: Model 1 was implemented with age, clinical variables (hallucinations/psychosis, depression, anxiety, apathy, sleep problems, FOG), and gait features, while Model 2, including only the subgroup performing PET, was implemented with PET variables combined with the top five features of the former model.ResultsSeventy-five PD patients were enrolled (33 PD-MCI and 42 noPD-MCI). PD-MCI vs. noPD-MCI resulted in older and showed worse gait patterns, mainly characterized by increased dynamic instability and reduced step length; when comparing amyloid PET data, the two groups did not differ. Regarding the machine learning analyses, evaluation metrics were satisfactory for Model 1 overcoming 80% for accuracy and specificity, whereas they were disappointing for Model 2.ConclusionsThis study demonstrates that machine learning implemented with specific clinical features and gait variables exhibits high accuracy in predicting PD-MCI, whereas amyloid PET imaging is not able to increase prediction. Additionally, our results prompt that a data mining approach on certain gait parameters might represent a reliable surrogate biomarker of PD-MCI.

Many recent studies have highlighted that the harmony of physiological walking is based on a specific proportion between the durations of the phases of the gait cycle. When this proportion is close to the so-called golden ratio (about 1.618), the gait cycle assumes an autosimilar fractal structure. In stroke patients this harmony is altered, but it is unclear which factor is associated with the ratios between gait phases because these relationships are probably not linear. We used an artificial neural network to determine the weights associable to each factor for determining the ratio between gait phases and hence the harmony of walking. As expected, the gait ratio obtained as the ratio between stride duration and stance duration was found to be associated with walking speed and stride length, but also with hip muscle forces. These muscles could be important for exploiting the recovery of energy typical of the pendular mechanism of walking. Our study also highlighted that the results of an artificial neural network should be associated with a reliability analysis, being a non-deterministic approach. A good level of reliability was found for the findings of our study.

Progressive pseudorheumatoid dysplasia (PPRD) is an autosomal recessive inherited skeletal dysplasia characterized by progressive non-inflammatory arthropathy affecting primarily the articular cartilage. Currently, little is known about the functional musculoskeletal aspects of these patients. In particular, an abnormal gait pattern has been described, without a clear hypothesis of the underlying causes in terms of muscular activity. This study presents the case of two siblings, 4 and 9 years old, a boy and a girl, respectively, suffering from PPRD at different stages of the disease. In addition to the clinical assessment, an instrumental gait analysis was performed. Swelling of the interphalangeal finger joints and fatigue were present in both cases. Gait abnormalities consisted of a relevant reduction in the ankle plantarflexion in the terminal phase of the gait cycle, associated with reduced gastrocnemius EMG activity and increased activity of the tibialis anterior, resulting in overloading at the initial peak of ground reaction forces. Gait anomalies observed were similar in both siblings with PPRD, although at different ages, and confirm walking patterns previously described in the literature. The calf muscle strength deficit and reduced activity during the stance phase of gait present in these two siblings indicate the typical absence of the propulsive phase. A stomping gait pattern, with the foot striking the ground hard on each step, was originally described. Further neurophysiological investigations are required to determine the origin of muscle weakness.

Parkinson's disease is the second most common neurodegenerative disorder in the world. Assumed that gait dysfunctions represent a major motor symptom for the pathology, gait analysis can provide clinicians quantitative information about the rehabilitation outcome of patients. In this scenario, wearable inertial systems for gait analysis can be a valid tool to assess the functional recovery of patients in an automatic and quantitative way, helping clinicians in decision making. Aim of the study is to evaluate the impact of the short-term rehabilitation on gait and balance of patients with Parkinson's disease. A cohort of 12 patients with Idiopathic Parkinson's disease performed a gait analysis session instrumented by a wearable inertial system for gait analysis: Opal System, by APDM Inc., with spatial and temporal parameters being analyzed through a statistic and machine learning approach. Six out of fourteen motion parameters exhibited a statistically significant difference between the measurements at admission and at discharge of the patients, while the machine learning analysis confirmed the separability of the two phases in terms of Accuracy and Area under the Receiving Operating Characteristic Curve. The rehabilitation treatment especially improved the motion parameters related to the gait. The study shows the positive impact on the gait of a short-term rehabilitation in patients with Parkinson's disease and the feasibility of the wearable inertial devices, that are increasingly spreading in clinical practice, to quantitatively assess the gait improvement.

No consensus exists on how to model human articulations within MSK models for the analysis of gait dynamics. We propose a method to evaluate joint models and we apply it to three models with different levels of personalization. The method evaluates the joint model’s adherence to the MSK hypothesis of negligible joint work by quantifying ligament and cartilage deformations resulting from joint motion, to be anatomically consistent, these deformations should be minimum. The contrary would require considerable external work to move the joint, violating a strong working hypothesis and raising concerns about the credibility of the MSK outputs. Gait analysis and medical resonance imaging (MRI) from ten participants were combined to build lower limb subject-specific MSK models. MRI-reconstructed anatomy enabled three levels of personalization using different ankle joint models, in which motion corresponded to different ligament elongation and cartilage co-penetration. To estimate the impact of anatomical inconsistency in MSK outputs, joint internal forces resulting from tissue deformations were computed for each joint model and MSK simulations were performed ignoring or considering their contribution. The three models differed considerably for maximum ligament elongation and cartilage co-penetration (between 5.94 and 50.69% and between −0.53 and −5.36 mm, respectively). However, the model dynamic output from the gait simulations were similar. When accounting for the internal forces associated with tissue deformation, outputs changed considerably, the higher the personalization level the smaller the changes. Anatomical consistency provides a solid method to compare different joint models. Results suggest that consistency grows with personalization, which should be tailored according to the research question. A high level of anatomical consistency is recommended when individual specificity and the behavior of articular structures is under investigation.

Total ankle prosthesis as a surgical solution in the case of end-stage osteoarthritis has seen a considerable increase in the last two decades. This study protocol arises from the need to understand the in vivo kinematics of mobile-bearing, flat tibial component total ankle replacement, evaluating the real range of motion and the reciprocal relationships between the components during normal motor tasks through the use of model-based radio-stereometric analysis (MB-RSA). In addition, pre- and post-operative evaluation of walking kinematics with inertial motion sensors, proprioception through a dedicated workstation, and clinical outcomes are discussed. We expect that based on our study protocol researchers will be able to improve future prosthetic designs and validate the setup of MB-RSA, as well as to understand “how an ankle prosthesis moves” once implanted in the patient.

Hereditary Spastic Paraplegia (HSP) is a rare inherited neurological disorder, whose predominant feature is a spastic gait. Gait analysis represents an objective tool to quantify the impairment of gait pattern in patients with HSP, thus supporting diagnosis and monitoring of disease progression. This study contributes to the characterization of HSP pathological gait, providing the assessment of test-retest repeatability of 122 parameters regarding postural sway, anticipatory postural adjustment in step initiation, gait and turn tasks. Data are collected on a cohort of thirty-five HSP patients, performing three consecutive repetitions of the Instrumented Stand and Walk (iSAW) test provided by Mobility Lab gait analysis system by APDM. Intraclass Correlation Coefficient (ICC) is used to assess repeatability. Repeatability Limit (RL) has also been evaluated and compared to the absolute value of difference (DoM) of HSP patients' measurements mean and normative mean of the same variable, in order to understand which variable can better characterize HSP gait with respect to normal gait. Results show that gait and turn measurements are more repeatable than sway and anticipatory postural adjustments variables. Furthermore, this study confirms previous findings in this field, identifying, among other gait parameters, cadence, gait velocity, stride length and RoM of the shanks as the main distinctive parameters of the pathology. Conversely, the RoM of the knees presents excellent repeatability, but low difference between healthy and pathological subjects.

The objective of the present study was to describe gait parameters of progressive supranuclear palsy (PSP) phenotypes at early stage verifying the ability of gait analysis in discriminating between disease phenotypes and between the other variant syndromes of PSP (vPSP) and Parkinson's disease (PD). Nineteen PSP (10 PSP-Richardson's syndrome, five PSP-parkinsonism, and four PSP-progressive gait freezing) and nine PD patients performed gait analysis in single and dual tasks. Although phenotypes showed similar demographic and clinical variables, Richardson's syndrome presented worse cognitive functions. Gait analysis demonstrated worse parameters in Richardson's syndrome compared with the vPSP. The overall diagnostic accuracy of the statistical model during dual task was almost 90%. The correlation analysis showed a significant relationship between gait parameters and visuo-spatial, praxic, and attention abilities in PSP-Richardson's syndrome only. vPSP presented worse gait parameters than PD. Richardson's syndrome presents greater gait dynamic instability since the earliest stages than other phenotypes. Computerized gait analysis can differentiate between PSP phenotypes and between vPSP and PD.

Objective: To compare results of the observational Wisconsin Gait Scale (WGS) and global gait indexes such as Gait Deviation Index (GDI) and Gait Variability Index (GVI), constituting an objective method of assessing gait, and taking into account parameters identified during 3-dimensional gait analysis (3DGA). Design: A validation study. Setting: Rehabilitation clinic. Participants: A total of 50 individuals poststroke and 50 individuals without stroke and without gait disorders (N=100). Interventions: Not applicable. Main Outcome Measures: Gait was evaluated using the WGS. GDI and GVI values were acquired using a movement analysis system. The global gait indexes GDI and GVI were determined based on the kinematic and spatiotemporal parameters, respectively. Results: The study showed statistically significant correlations between the parameters of GDI affected leg and WGS total score (R=-0.87), GVI affected leg and WGS total score (R=-0.93), GVI unaffected leg and WGS total score (R=-0.88), GVI affected/unaffected leg and the total score in the assessment of spatiotemporal parameters on the WGS (R=-0.81) as well as GDI affected leg and the total score in the assessment of kinematics parameters on the WGS (R=-0.85). All correlations were strong (0.7

Nociplastic pain has been introduced by the IASP as a third category of pain, distinct from nociceptive and neuropathic pain. Pathogenetically, it is considered to be a continuum of these two types of pain after becoming chronic. Repetitive peripheral painful stimulation causes a central sensitization with hypersensitivity of the corresponding spinal metamer or brain region. Therefore, signs of altered nociception, such as allodynia, may be found on the tissues of the related dermatome, myotome and sclerotome, and characterize nociplastic pain. This kind of pain was found in over 20% of people with multiple sclerosis (pwMS), a demyelinating autoimmune disease that affects the central nervous system. Nociplastic pain may be an amplifier of spasticity, the main pyramidal symptom that affects about 80% of pwMS. This article details the case of a 36-year-old woman with multiple sclerosis who was affected by spasticity and non-specific pain of the lower limbs, disabling on walking. Previous analgesic and muscle relaxant treatment had no benefits. The diagnosis of nociplastic pain on the cutaneous tissue of the anterolateral region of the left thigh and its treatment with intradermal normal saline injection on the painful skin area showed immediate and lasting effects on pain and spasticity, improving significantly the patient’s balance and walking, as assessed by a 3D motion analysis and rating scales.

The recovery of independent gait represents one of the main functional goals of the rehabilitative interventions after stroke but it can be hindered by the presence of unilateral spatial neglect (USN). The aim of the paper is to study if the presence of USN in stroke patients affects lower limb gait parameters between the two body sides, differently from what could be expected by the motor impairment alone, and to explore whether USN is associated to specific gait asymmetry. Thirty-five stroke patients (right or left lesion and ischemic or hemorrhagic etiology) who regained independent gait were assessed for global cognitive functioning and USN. All patients underwent a gait analysis session by using a wearable inertial system, kinematic parameters were computed. Enrolled patients presented altered motion parameters. Stroke patients with USN showed specific asymmetries in the following parameters: stance phase, swing phase, and knee range of motion. No differences in the clinical scores were found as the presence of USN. The presence of USN was associated with a specific form of altered gait symmetry. These findings may help clinicians to develop more tailored rehabilitative training to enhance gait efficacy of patients with motor defects complicated by the presence of selected cognitive impairments. Overview of the experiment setup. The workflow shows: diagnosis of unilateral spatial neglect by the neuropsychologist, sensors placement, gait analysis protocol and evaluation of the gait asymmetry together with the statistically significant features.

Background Walking on compliant surfaces, on sand in particular, is now recommended for training in both elderlies and injured subjects/individuals, allowing to perform high intensity exercises (i.e. augmented energy expenditure) in safe conditions (i.e. minimizing the impact on the joints and the risk of fall). Nevertheless, despite the assessment of energetics of walking on sand, the quantitative biomechanical characterization of walking on sand in ecological conditions is largely lacking. Research question Which is the effect of sand surface on gait speed, gait temporal segmentation and their variability as related to surface compliance in ecological condition? Methods Eighteen healthy adults were assessed while walking on solid ground, dry-, and wet sand in ecological conditions by means of wearable inertial sensors (Miniwave, Cometa s.r.l., Italy). The best performing algorithm for the segmentation of walking on sand was selected among 17 algorithms designed for solid ground. Gait timing (i.e. speed, temporal segmentation, variability) was analysed, for the first time, with respect to sand compliance, and compared to walking on solid ground. Results Self-selected speed on a 60 m distance increased when walking on sand with respect to solid ground (Median 1.02 m/s), with the highest speed on wet sand (Median 1.15 m/s). A stabilizing strategy on the uneven surface provided by sand was highlighted by i) increased stance and double support durations with respect to speed on wet sand, and ii) increased short-term variability of stride, corresponding to continual adjustments of the lower limbs due to shifting surface provided by sand. Significance This study represents the first step in the objective characterization of walking on compliant surfaces as sand, necessary for the definition of training and rehabilitative programs.

Background: Parkinson’s disease is the second most frequent neurodegenerative disorder. Its diagnosis is challenging and mainly relies on clinical aspects. At present, no biomarker is available to obtain a diagnosis of certainty in vivo. Objective: The present review aims at describing machine learning algorithms as they have been variably applied to different aspects of Parkinson’s disease diagnosis and characterization. Methods: A systematic search was conducted on PubMed in December 2019, resulting in 230 publications obtained with the following search query: “Machine Learning” “AND” “Parkinson Disease”. Results: The obtained publications were divided into 6 categories, based on different application fields: “Gait Analysis - Motor Evaluation”, “Upper Limb Motor and Tremor Evaluation”, “Handwriting and typing evaluation”, “Speech and Phonation evaluation”, “Neuroimaging and Nuclear Medicine evaluation”, “Metabolomics application”, after excluding the papers of general topic. As a result, a total of 166 articles were analyzed after elimination of papers written in languages other than English or not directly related to the selected topics. Conclusion: Machine learning algorithms are computer-based statistical approaches that can be trained and are able to find common patterns from big amounts of data. The machine learning approaches can help clinicians in classifying patients according to several variables at the same time.

Background Spasticity in people with Multiple Sclerosis (pwMS) is one of the most disabling symptoms on walking ability and balance. Among the systemic antispastic drugs, Nabiximols showed a good tolerability, safety profile and relevant efficacy. A few studies assessed long-term effects of this drug through clinical scales and instrumental tools, but no study investigated short-term effects. The aim of our study is to quantitatively evaluate the immediate effects of Nabiximols on walking and balance and their maintenance after 4 weeks in pwMS and spasticity. Methods pwMS were enrolled and randomized in 2 treatment groups: Sativex (SG) and control (CG) group. All patients were assessed at T0 (before the first Sativex puff), T1(after 45 minutes) and T2 (after 4 weeks of treatment) using clinical scales and 3d-Gait Analysis . Then, the patients treated with Sativex, were divided into 5 subgroups according to Numeric Rating Scale for spasticity (NRSs) and Berg Balance Score (BBS) response: NRSs responder[1] and non-[2]; BBS responders[3] and non-[4]; NRSs-BBS responders[5]. Results 32 pwMS (22 SG, 10 CG) were recruited. Significant improvements were found between T0 and T1 in SG compared to CG in a few clinical and kinematic parameters. Larger significant differences were found for NRSs and BBS responders’ groups versus CG. Eventually, no significant differences were found comparing the results between T1 and T2, suggesting the persistence of the improvements emerged at T1. Conclusion These results quantitatively demonstrated a short time effect of Nabiximols on balance and walking of pwMS, which is mantained after 4 weeks. Patients identified as responder by combination of NRSs and BBS showed the best efficacy. These findings may suggest how to early select the real responders in order to improve the adherence and cost-effectiveness of the therapy.

Amputation of a lower limb implies a re-organization in the strategies used to reach a stable walking pattern. The planar covariation law of elevation angles is a well-defined low-dimensional description of the kinematics of movement; according to this law, thigh, shank and foot elevation angle co-vary on a plane, defining a typical gait loop. However, a robust biomechanical interpretation of the outcomes of its related analysis is still missing. In this work, we tested the planar covariation law on a group of 14 trans-femoral amputees, comparing the results with the ones related to 12 healthy people. Moreover, by adopting a common covariance plane for all the subjects, we checked whether the projection of the original elevation angles on this plane is able to yield biomechanically meaningful information on the control of prosthetic gait. A common plane was able to describe the coordination of lower limb elevation angles in all subjects; on this plane, most of the differences among populations were identified on the time course of one principal component.

Introduction: The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings. Areas covered: Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings. Expert opinion: IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

Total Hip Arthroplasty (THA) is the gold standard for hip replacement surgery. It can be performed with two different kinds of prostheses: cemented and uncemented. The surgeons have always decided on the type of prosthesis based on the age, sex of the patient and bone stock on x rays. In this paper 42 subjects underwent THA and performed both gait analysis and bone mineral density (BMD) evaluation through CT scans; spatial and temporal gait parameters were used to predict BMD of the distal and proximal parts of the femur before and one year after surgery using machine learning regression analysis. A simple linear regression (LR) and k-nearest neighbor (KNN) were implemented coding with Python Scikit-Learn libraries and some evaluation metrics were computed: the coefficient of determination (R2), mean absolute error, mean squared error and root mean squared error. Both the algorithms had a R2 greater than 75% in predicting both proximal and distal; particularly, LR obtained the highest score of 88.4% in predicting the BMD before the THA and of 81.3% after the THA. All the R2 of KNN ranged from 75% and 77%. All the calculated errors were always below 0.001. In conclusion, this research shows the feasibility of gait parameters for assessing the follow-up after 52 weeks of patients undergoing THA by predicting the BMD. Moreover, the results give insights about the relationship between the patterns of gait and BMD.

Background Gait disturbances are typical of persons with idiopathic normal pressure hydrocephalus (iNPH) without signs distinctive from other neurodegenerative and vascular conditions. Cerebrospinal fluid tap-test (CSF-TT) is expected to improve the motor performance of iNPH patients and is a prognostic indicator in their surgical management. This observational prospective study aims to determine which spatio-temporal gait parameter(s), measured during instrumented motor tests, and clinical scale(s) may provide a relevant contribution in the evaluation of motor performance pre vs. post CSF-TT on iNPH patients with and without important vascular encephalopathy. Methods Seventy-six patients (20 with an associated vascular encephalopathy) were assessed before, and 24 and 72 h after the CSF-TT by a timed up and go test (TUG) and an 18 m walking test (18 mW) instrumented using inertial sensors. Tinetti Gait, Tinetti Balance, Gait Status Scale, and Grading Scale were fulfilled before and 72 h after the CSF-TT. Stride length, cadence and total time were selected as the outcome measures. Statistical models with mixed effects were implemented to determine the relevant contribution to response variables of each quantitative gait parameter and clinical scales. Results and conclusion From baseline to 72 h post CSF-TT patients improved significantly by increasing cadence in 18 mW and TUG (on average of 1.7 and 2.4 strides/min respectively) and stride length in 18 mW (on average of 3.1 cm). A significant reduction of gait apraxia was reflected by modifications in double support duration and in coordination index. Tinetti Gait, Tinetti Balance and Gait Status Scale were able to explain part of the variability of response variables not covered by instrumental data, especially in TUG. Grading Scale revealed the highest affinity with TUG total time and cadence when considering clinical scales alone. Patients with iNPH and an associated vascular encephalopathy showed worst performances compared to pure iNPH but without statistical significance. Gait improvement following CSF-TT was comparable in the two groups. Overall these results suggest that, in order to augment CSF-TT accuracy, is key to assess the gait pattern by analyzing the main spatio-temporal parameters and set post evaluation at 72 h. Trial registration Approved by ethics committee: CE 14131 23/02/2015.

Parkinson’s Disease (PD) is a common neurodegenerative disorder whose clinical picture is characterized by motor and non-motor symptoms. One of motor symptoms is freezing of gait (FoG) that consists in a few seconds during which patients can't start to walk again. In this paper 41 patients affected by PD, with and without FoG, underwent gait analysis performing three gait tasks: normal gait, a motor dual task and a cognitive task. A statistical analysis was performed on clinical, demographical and on the spatial and temporal parameters in order to find any difference between PD patients with and without FoG; the last one obtained no statistically significant results. Thus, a machine learning analysis was implemented employing tree-based algorithms (decision tree, Random Forests, Gradient Boosted Tree, Ada-Boosting of a decision tree) and using as input the spatial and temporal features of gait. The results were promising since accuracy, specificity and sensitivity overcame 90%, reaching also 100% of sensitivity in some cases. The best algorithms were Gradient Boosted Tree and the Ada-Boosting of a decision tree while Random Forests and decision tree obtained lower results. This study proved that machine learning can help to identify patients affected by mild form of FoG that exposes them to a major risk of developing more severe form of freezing with a consequent increased risk of falling.

Although a very large number of students in the world use uncomfortable and heavy backpacks, their negative influence on gait in terms of spatiotemporal and kinematic parameters are still not well investigated. The purpose of the paper is to investigate the role of the school backpack during the execution of the Timed Up and Go test trying to identify if and how much it affects walking in terms of spatiotemporal and kinematic parameters considering whether it might be correlated to low back pain in children. A population-based sample of 98 children students ages 10-12 years was studied; gender, age, weight and lower limb length were recorded. Data were computed using a wearable inertial device for gait analysis: G-Walk System by BTS Bioengineering and analyzed through Inferential Statistics and Machine Learning. Overall, concerning Inferential Statistics carried out through ANOVA test for each motion parameter between free walk and walk with backpack, it was found that there is a significant statistical difference on 23 out of 30 motion parameters, of which 20 with maximum statistical significance (p

Background: Total ankle arthroplasty is intended to restore physiological joint function in case of severe ankle arthritis. However, little is known about the functional outcome associated to different prosthesis designs. The aim of this retrospective study was to compare clinical and functional outcomes via gait analysis of two ankle prostheses designed to preserve ankle ligamentous isometry. Methods: Two groups of twenty patients who underwent ankle arthroplasty using either a three-component or a two-component prosthesis, were clinically evaluated, both pre-operatively and at minimal 2-year follow-up, by means of the AOFAS score. The spatio-temporal parameters, along with the kinetics and kinematics of the lower limb joints were also assessed at follow-up via gait analysis. The non-parametric Kruskal-Wallis test was used to assess differences in functional data between the two patient groups and with respect to those from a control group of 20 healthy subjects. Findings: All AOFAS scores significantly improved from pre-operative to post-operative assessment in both patient groups (P < 0.05). Most spatio-temporal and functional parameters in the patients were worse than those in the control group, but no significant differences were observed between the two arthroplasty groups. Interpretation: Both patient groups showed improved clinical outcome at follow-up, with a few differences in gait parameters. However, neither of the two groups achieved normal locomotion patterns. Since both prostheses were designed to preserve ligamentous isometry, the choice of one implant over the other should be due to preferences in the surgical approach and to other patient-specific factors.

Spasticity is a common pathology after brain lesions consisting in an incorrect synergic contraction of agonist-antagonist muscles. Nowadays, there are more treatments, yet recently a new therapy was introduced: the injections of botulinum toxin in the spastic muscles. This work is a pilot study aiming to analyse quantitatively these co-activations before and after the treatment. Data were acquired performing gait analysis in the laboratory of Salerno’s hospital. Spatial temporal parameters, kinematic information and electromyography signals were obtained. Two patients were analysed and a Matlab application was implemented to calculate a co-activation index and the time of co-activation of some muscular couples. The comparison between the results before and after the treatment describes a positive prognosis with improvements in spatial temporal parameters and kinematic for both patients. Both the co-activation index and the times of co-activations decreased after the treatment. This pilot study shows that patients treated with BTX have a positive prognosis with a quantitative improving.

Parkinson’s Disease is one of the most common neurodegenerative disorders. Its principal symptoms regard motor area, and gait is one of the most affected motor characteristics. In clinical environment Parkinsonian gait is often assessed through gait analysis. Opal System by APDM is a commercial device used to perform gait analysis with inertial measurements units (IMUs). In this study we evaluate repeatability of spatio-temporal gait measurements, assessed with Opal Instrumented Stand and Walk (ISAW) test on a cohort of forty-five Parkinsonian patients. Repeatability is assessed by means of Intraclass Correlation Coefficient (ICC) and Repeatability Limit (RL) for each variable. RL is then compared to the absolute value of difference (DoM) of PD patients’ measurements mean and normative mean of the same variable, in order to understand which variable can better characterize Parkinsonian gait with respect to normal gait. Results show that gait and turn measurements are more repeatable than sway and anticipatory postural adjustments variables, and they are proper indexes to better identify Parkinsonian walking features.

Although a very large number of students in the world use uncomfortable and heavy backpacks, their negative musculoskeletal effects on gait and posture are still not well investigated. Aim of the paper has been the study of differences affecting the kinematic gait parameters during free walk and walk with backpack to evaluate their potential influence on skeletal-muscle disorders. Gait recordings in both conditions on 50 healthy volunteers participating students have been performed by a G-WALK inertial system calculating the main kinematic parameters namely Propulsion index and Initial Double Support, Stance and Swing Phases. ANOVA results between both walking conditions showed that all gait cycle studied values are significantly negatively affected by walking with backpack supposing a potential biomechanical overload on skeletal muscle structures in students exposed to these prolonged conditions.

Introduction Parkinson's disease (PD) is the second most common neurodegenerative disorder in the world, while Progressive Supranuclear Palsy (PSP) is an atypical Parkinsonism resembling PD, especially in early stage. Assumed that gait dysfunctions represent a major motor symptom for both pathologies, gait analysis can provide clinicians with subclinical information reflecting subtle differences between these diseases. In this scenario, data mining can be exploited in order to differentiate PD patients at different stages of the disease course and PSP using all the variables acquired through gait analysis. Methods A cohort of 46 subjects (divided into three groups) affected by PD patients at different stages and PSP patients was acquired through gait analysis and spatial and temporal parameters were analysed. Synthetic Minority Over-sampling Technique was used to balance our imbalanced dataset and cross-validation was applied to provide different training and testing sets. Then, Random Forests and Gradient Boosted Trees were implemented. Results Accuracy, error, precision, recall, specificity and sensitivity were computed for each group and for both algorithms, including 16 features. Random Forests obtained the highest accuracy (86.4%) but also specificity and sensitivity were particularly high, overcoming the 90% for PSP group. Conclusion The novelty of the study is the use of a data mining approach on the spatial and temporal parameters of gait analysis in order to classify patients affected by typical (PD) and atypical Parkinsonism (PSP) based on gait patterns. This application would be helpful for clinicians to distinguish PSP from PD at early stage, when the differential diagnosis is particularly challenging.

Objective: To quantify gait abnormalities in people with Dravet syndrome (DS). Methods: Individuals with a confirmed diagnosis of DS were enrolled, and stratified according to knee flexion at initial contact (IC) and range of motion (ROM) during stance (atypical crouch: knee flexion >20° at IC and knee ROM >15° during stance; straight: knee flexion

Musculoskeletal radiology has been mostly limited by the option between imaging under load but in two dimensions (i.e., radiographs) and three-dimensional (3D) scans but in unloaded conditions (i.e., computed tomography [CT] and magnetic resonance imaging in a supine position). Cone-beam technology is now also a way to image the extremities with 3D and weight-bearing CT. This article discusses the initial experience over a few studies in progress at an orthopaedic center. The custom design of total ankle replacements, the patellofemoral alignment after medial ligament reconstruction, the overall architecture of the foot bones in the diabetic foot, and the radiographic assessment of the rearfoot after subtalar fusion for correction of severe flat foot have all taken advantage of the 3D and weight-bearing feature of relevant CT scans. To further support these novel assessments, techniques have been developed to obtain 3D models of the bones from the scans and to merge these with state-of-the-art gait analyses.

Quantitative evaluation of gait has been considered a useful tool with which to identify subtle signs of motor system peculiarities in autism spectrum disorder (ASD). However, there is a paucity of studies reporting gait data in ASD as well as investigating learning processes of locomotor activity. Novel advanced technologies that couple treadmills with virtual reality environments and motion capture systems allows the evaluation of gait patterns on multiple steps and the effects of induced gait perturbations, as well as the ability to manipulate visual and proprioceptive feedbacks. This study aims at describing the gait pattern and motor performance during discrete gait perturbation of drug-naive, school-aged children with ASD compared to typically developing (TD) peers matched by gender and age. Gait analysis was carried out in an immersive virtual environment using a 3-D motion analysis system with a dual-belt, instrumented treadmill. After 6 min of walking, 20 steps were recorded as baseline. Then, each participant was exposed to 20 trials with a discrete gait perturbation applying a split-belt acceleration to the dominant side at toe-off. Single steps around perturbations were inspected. Finally, 20 steps were recorded during a post-perturbation session. At baseline, children with ASD had reduced ankle flexion moment, greater hip flexion at the initial contact, and greater pelvic anteversion. After the discrete gait perturbation, variations of peak of knee extension significantly differed between groups and correlated with the severity of autistic core symptoms. Throughout perturbation trials, more than 60% of parameters showed reliable adaptation with a decay rate comparable between groups. Overall, these findings depicted gait peculiarities in children with ASD, including both kinetic and kinematic features; a motor adaptation comparable to their TD peers, even though with an atypical pattern; and a motor adaptation rate comparable to TD children but involving different aspects of locomotion. The platform showed its usability with children with ASD and its reliability in the definition of paradigms for the study of motor learning while doing complex tasks, such as gait. The additional possibility to accurately manipulate visual and proprioceptive feedback will allow researchers to systematically investigate motor system features in people with ASD.

Despite the growing use of different wearable inertial systems for gait analysis in clinical setting, also based on a different sensor placement, there is still a lack of knowledge about the agreement between them and their repeatability. The purpose of this study is to investigate the agreement between two commercial wearable inertial systems for gait analysis: Opal and G-Walk Systems, and their repeatability. Fifty-three subjects, healthy and pathological, underwent a gait analysis session instrumented by both systems, seven spatiotemporal parameters were recorded. The study of agreement was carried out through Bland-Altman Analysis, Passing-Bablok regression and Paired t-test, the study of repeatability through the intra class correlation coefficient ICC(3,1). Study results showed a not perfect agreement between the two systems although they both showed good repeatability. This work underlines the importance to perform a study of agreement before using devices interchangeably or even as a replacement in order to have reliable measurements.

Hip dysplasia patients after total hip replacement show worse functional performance compared to primary osteoarthritis patients, and unfortunately there is no research on muscle and joint loads that would help understand rehabilitation effects, motor dysfunctions and failure events. We tested the hypothesis that a higher functional improvement in hip dysplasia patients who received hip abductor strengthening after hip replacement, would result in different gait function and musculoskeletal loads during walking compared to patients who performed standard rehabilitation only. In vivo gait analysis and musculoskeletal modeling were used to analyze the differences in gait parameters and hip and muscle forces during walking between the two groups of patients. We found that, in a functional scenario of very mild abnormalities, the patients who performed muscle strengthening expressed a more physiological force pattern and a generally greater force in the operated limb, although statistically significant in limited portions of the gait cycle, and likely related to a higher gait speed. We conclude that in a low-demand task, the abductor strengthening program does not have a marked effect on hip loads, and further studies on hip dysplasia patients would help clarify the effect of muscle strengthening on loads.

Gait impairments are among the most disabling symptoms in several musculoskeletal and neurological conditions, severely limiting personal autonomy. Wearable gait sensors have been attracting attention as diagnostic tool for gait and are emerging as promising tool for tutoring and guiding gait execution. If their popularity is continuously growing, still there is room for improvement, especially towards more accurate solutions for spatio-temporal gait parameters estimation. We present an implementation of a zero-velocity-update gait analysis system based on a Kalman filter and off-the-shelf shoe-worn inertial sensors. The algorithms for gait events and step length estimation were specifically designed to comply with pathological gait patterns. More so, an Android app was deployed to support fully wearable and stand-alone real-time gait analysis. Twelve healthy subjects were enrolled to preliminarily tune the algorithms; afterwards sixteen persons with Parkinson's disease were enrolled for a validation study. Over the 1314 strides collected on patients at three different speeds, the total root mean square difference on step length estimation between this system and a gold standard was 2.9%. This shows that the proposed method allows for an accurate gait analysis and paves the way to a new generation of mobile devices usable anywhere for monitoring and intervention. ispartof: IEEE Transactions on Neural Systems and Rehabilitation Engineering vol:24 issue:7 pages:764-773 ispartof: location:United States status: published

The aim of the study was to investigate the biometrical quality of a newly developed activity monitor (uSense) to document established physical activity (PA) parameters as well as innovative qualitative and quantitative gait characteristics for habitual activity behavior in multi-morbid, older adults. Validity, test-retest reliability, and feasibility of established (including activity counts, MET-Intensities, number/duration of gait episodes/steps) as well as newly developed gait characteristics, which have not been documented before for habitual assessment (including number, velocity, duration of turnings, various parameters for gait symmetry/ regularity), have been analyzed for multimorbid, geriatric patients with cognitive impairment (n=110) discharged from ward-based rehabilitation. On average, Spearman correlations of established and innovative uSense parameters with clinically relevant parameters were high for motor performances (range for rhos: 0.02 – 0.63) and life space (0.01 – 0.59) and low to moderate for cognitive status (0.01 – 0.25), and age (0.01 – 0.30), indicating moderate to good construct validity. Concurrent validity was high as PA parameters measured by the U-Sense monitor showed consistently high correlation with equivalent parameters measured by another well-established ambulatory motion sensor (PAMSysTM) (0.59 – 0.91). Moderate to excellent test-retest reliability was shown for all uSense parameters (ICC: 0.68–0.97) and good feasibility could be shown, as 85.5% of all measurements were completed without failure. The uSense monitor allows documentation of established and innovative qualitative-quantitative parameters for habitual PA behavior which have so far only been assessed in laboratory settings in multi-morbid, cognitively impaired, older adults with moderate to good validity and high test-retest reliability.

Background. The use of rhythmic auditory stimulation (RAS) has been proven useful in the management of gait disturbances associated with Parkinson’s disease (PD). Typically, the RAS consists of metronome or music-based sounds (artificial RAS), while ecological footstep sounds (ecological RAS) have never been used for rehabilitation programmes. Objective. The aim of the present study was to compare the effects of a rehabilitation programme integrated either with ecological or with artificial RAS. Methods. An observer-blind, randomized controlled trial was conducted to investigate the effects of 5 weeks of supervised rehabilitation integrated with RAS. Thirty-eight individuals affected by PD were randomly assigned to one of the two conditions (ecological vs. artificial RAS); thirty-two of them (age 68.2 ± 10.5, Hoehn and Yahr 1,5–3) concluded all phases of the study. Spatio-temporal parameters of gait and clinical variables were assessed before the rehabilitation period, at its end, and after a 3-month follow-up. Results. Thirty-two participants were analyzed. The results revealed that both groups improved in the majority of biomechanical and clinical measures, independently of the type of sound. Moreover, exploratory analyses for separate groups were conducted, revealing improvements on spatio-temporal parameters only in the ecological RAS group. Conclusions. Overall, our results suggest that ecological RAS is equally effective compared to artificial RAS. Future studies should further investigate the role of ecological RAS, on the basis of information revealed by our exploratory analyses. Theoretical, methodological and practical issues concerning the implementation of ecological sounds in the rehabilitation of PD patients are discussed. Trial Registration. ClinicalTrials.gov, NCT03228888

Muscle coactivation is the mechanism that regulates the simultaneous activity of antagonist muscles around the same joint. During walking, muscle joint coactivation varies within the gait cycle according to the functional role of the lower limb joints. In the present study, we used a time-varying multi-muscle coactivation function (TMCf) with the aim of investigating the coactivation of 12 lower limb muscles and its relationship with the gait cycle, gait speed (low, self-selected, and fast), ground reaction force, gait variability, and mechanical energy consumption, and recovery in a sample of 20 healthy subjects. Results show that the TMCf is speed dependent and highly repeatable within and between subjects, similar to the vertical force profile, and negatively correlated with energy recovery and positively correlated with both energy consumption and balance-related gait parameters. These findings suggest that the global lower limb coactivation behavior could be a useful measure of the motor control strategy, limb stiffness, postural stability, energy efficiency optimization, and several aspects in pathological conditions.

Gli obiettivi principali dell’Artroprotesi Totale d’Anca (ATA) sono la riduzione del dolore e il ripristino della normale escursione articolare. Una limitata escursione, imputabile a fattori come il disegno protesico e il rapporto testa-collo, è spesso causa di disabilità. Questi fattori sono stati studiati in-vitro ma il ruolo dei tessuti molli e la reale capacità del paziente con ATA di eseguire movimenti estremi all’anca è ancora ignota. L’obiettivo di questo studio è di valutare tramite gait analysis e video-fluoroscopia 3D se l’escursione articolare è limitata dal contatto o dai tessuti molli, e come tale limitazione sia correlata con il rapporto testa-collo.

The aim of this review is to collect and discuss the current best evidence published in literature about the effect of the Masai Barefoot Technology(MBT) shoes on gait and muscle activation and try to draw conclusions on the possible benefits. We searched Medline, CINAHL, Embase and the Cochrane Central Registry of Controlled Trials. The reference lists of the previously selected articles were then examined by hand. Only studies comparing biomechanical and clinical outcomes were selected. Review, anatomical studies, letter to editor and instructional course were excluded. Finally, all the resulting articles were reviewed and discussed by all the authors to further confirm their suitability for this review: in the end, 22 articles were included. A total of 532 patients presenting a mean age of 34.3 years were studied. All patients evaluated were healthy or amateur sports except in two studies where only obese subjects and knee osteoarthritis patients were involved. Seven studies evaluated only male subjects, whereas four studies evaluated only female. Twelve of twenty-two studies performed electromyographic analyses. Weight was reported in 19 studies, whereas body mass index were reported only in a five studies. All studies reported kinematic analysis of shoe effects and compared the relationship between muscle recruitment and electromyographic activity. Unstable footwears were shown to immediately alter the stability in gait during daily-life activities. The center of body pressure is moved posteriorly with a consequent posterior displacement of the upper part of body in order to regain an appropriate body balance, and these postural changes are associated with an overall increase in the activity of lumbar erector spine muscles, as well as certain lower limb muscles. Current literature provides enough cues to conclude for a beneficial role of MBT shoes in the postural and proprioceptive recovery, but from the same literature cannot be drown clear and appropriate guidance to determine more in detail their indication for specific pathological conditions or for particular phases of the musculoskeletal recovery process.