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The manual lifting tasks, which occur in the vast majority of workplaces can cause work-related low-back disorders (WLBDs), that are the most common musculoskeletal problems. Recently, to identify the relationship between WLBDs and risk factors, wearable monitoring devices-based biomechanical risk assessments have been proposed. The purpose of this study is to characterize from a biomechanical point of view, using wearable devices other lifting conditions to define, in the future, a risk classification tool that can be applied in each lifting condition. To do this, we recorded electromyographic data of workers during lifting tasks designed to have a growing lifting index (LI=1,2 and 3) by means of revised NIOSH lifting equation. Each lifting condition (LI=1 or LI=2 or LI=3) was obtained in three different ways modifying the asymmetry angle. We acquired data by using Wi-Fi transmission surface electromyograph (sEMG). From the sEMG signals, analyses of time and frequency domains were performed within the lifitng cycle to extract maximum value, the average rectified value, the mean frequency defined as the gravity center frequency of the power spectrum of the signal. The results show that these sEMG data grew significantly with the LI and that all the lifting condition pairs are discriminated. We will test whether machine-learning techniques used for mapping features extracted from wearable sensors on LI levels can improve the biomechanical risk estimation during these tasks. These findings suggest the use of kinematic and sEMG features to assess biomechanical risk associate with work activities can be integrated with methods already used for biomechanical risk assessment.

The aim of the present study was to characterize and analyze the most important individual and organizational variables associated with job accommodation in subjects with degenerative cerebellar ataxia by administering a series of international and validated work activity-related scales. Twenty-four workers (W) and 58 non-workers (NW) were recruited: 34 with autosomal dominant ataxia and 48 with autosomal recessive ataxia (27 with Friedreich ataxia and 21 with sporadic adult-onset ataxia of unknown etiology). The severity of ataxia was rated using the Scale for the Assessment and Rating of Ataxia. Our results showed that the ataxic W were predominantly middle-aged (41-50 years), high school graduate, and married men with a permanent work contract, who had been working for more than 7 years. The W with ataxia exhibited a good level of residual working capacity, irrespective of gender, age range, and duration of the disease, and they were observed to have a low or average-to-low job stress-related risk. Supporting patients with ataxia to find an appropriate job is an important priority because about 78% of NW search for a job and W and NW have the same potential work abilities (no relevant differences were found in terms of disease characteristics, gender, and work resilience). In this view, introducing NW to work-life may have a potential rehabilitative aspect. Findings of this study highlight that equal job opportunities for subjects affected by cerebellar ataxia are recommended.

The present study's aim was to identify the kinematic and kinetic gait patterns and to measure the energy consumption in people with amputation according to both the anatomical level of amputation and the type of prosthetic components in comparison with a control group matched for the gait speed. Fifteen subjects with unilateral transtibial amputation (TTA), forty with unilateral transfemoral amputation (TFA) (9 with mechanical, 17 with CLeg and 14 with Genium prosthesis) and forty healthy subjects were recruited. We computed the time-distance gait parameters; the range of angular motion (RoM) at hip, knee and ankle joints, and at the trunk and pelvis; the values of the 2 peaks of vertical force curve; the full width at half maximum (FWHM) and center of activity (CoA) of vertical force; the mechanical behavior in terms of energy recovery (R-step) and energy consumption. The main results were: i) both TTA and TFA show a common gait pattern characterized by a symmetric increase of step length, step width, double support duration, pelvic obliquity, trunk lateral bending and trunk rotation RoMs compared to control groups. They show also an asymmetric increase of stance duration and of Peak1 in non-amputated side and a decrease of ankle RoM in amputated side; ii) only TFA show a specific gait pattern, depending on the level of amputation, characterized by a symmetric reduction of R-step and an asymmetric decrease of stance duration, CoA and FWHM and an increase of Peak1 in the amputated side and of hip and knee RoM, CoA and FWHM in the non-amputated side; iii) people with amputation with Genium prosthesis show a longer step length and increased hip and knee RoMs compared to people with amputation with mechanical prosthesis who conversely show an increased pelvic obliquity: these are specific gait patterns depending of the type of prosthesis. In conclusion, we identified both common and specific gait patterns in people with amputation, either regardless of, or according to their level of amputation and the type of prosthetic component.

Occupational exoskeletons are becoming a concrete solution to mitigate work-related musculoskeletal disorders associated with manual material handling activities. The rationale behind this study is to search for common ground for exoskeleton evaluators to engage in dialogue with corporate Health &amp, Safety professionals while integrating exoskeletons with their workers. This study suggests an innovative interpretation of the effect of a lower-back assistive exoskeleton and related performances that are built on the benefit delivered through reduced activation of the erector spinae musculature. We introduce the concept of “equivalent weight” as the weight perceived by the wearer, and use this to explore the apparent reduced effort needed when assisted by the exoskeleton. Therefore, thanks to this assistance, the muscles experience a lower load. The results of the experimental testing on 12 subjects suggest a beneficial effect for the back that corresponds to an apparent reduction of the lifted weight by a factor of 37.5% (the perceived weight of the handled objects is reduced by over a third). Finally, this analytical method introduces an innovative approach to quantify the ergonomic benefit introduced by the exoskeletons’ assistance. This aims to assess the ergonomic risk to support the adoption of exoskeletons in the workplace.

Biomechanical overload represents one of the main risks in the industrial environment and the main possible source of musculoskeletal disorders and diseases. The aim of the this study is to introduce new technologies for quantitative risk assessment of biomechanical overload, by integrating surface electromyography (sEMG) with an innovative motion-capture system based on inertial measurement units (IMU). The case study was carried out in collaboration with Fiat Chrysler Automobiles Italy S.p.A. and deals with the analysis of the “central tunnel cabinet assembly” activity, performed by two workers of assembly lines during a working task, which lasts about one minute. The electromyography signals were acquired bilaterally, in three different body regions on the right and on the left side of the Erector Spinae, during standard working activities; the progression of trunk postures (flexion-extension, lateral flexion and twisting) was tracked by using an inertial motion-capture system made of wearable inertial sensors, to evaluate the alignment of the major body segments, using a developed algorithm. Data analysis showed kinematic and muscular activity patterns consistent with the expected ones. In particular, data show that the proposed technologies can be integrated and simultaneously used during workers’ real performing activities. Data quality also demonstrates that both types of sensors, EMG electrodes and IMU, not influenced each other, neither by electromagnetic noise usually present in an industrial environment. The results of this study show feasibility and usefulness of the integration of kinematic and electromyography technologies for assessing the biomechanical overload in production lines.

Patients affected by neurological pathologies with motor disorders when they are of working age have to cope with problems related to employability, difficulties in working, and premature work interruption. It has been demonstrated that suitable job accommodation plans play a beneficial role in the overall quality of life of pathological subjects. A well-designed return-to-work program should consider several recent innovations in the clinical and ergonomic fields. One of the instrument-based methods used to monitor the effectiveness of ergonomic interventions is surface electromyography (sEMG), a multi-channel, non-invasive, wireless, wearable tool, which allows in-depth analysis of motor coordination mechanisms. Although the scientific literature in this field is extensive, its use remains significantly underexploited and the state-of-the-art technology lags expectations. This is mainly attributable to technical and methodological (electrode-skin impedance, noise, electrode location, size, configuration and distance, presence of crosstalk signals, comfort issues, selection of appropriate sensor setup, sEMG amplitude normalization, definition of correct sEMG-related outcomes and normative data) and cultural limitations. The technical and methodological problems are being resolved or minimized also thanks to the possibility of using reference books and tutorials. Cultural limitations are identified in the traditional use of qualitative approaches at the expense of quantitative measurement-based monitoring methods to design and assess ergonomic interventions and train operators. To bridge the gap between the return-to-work rehabilitation and other disciplines, several teaching courses, accompanied by further electrodes and instrumentations development, should be designed at all Bachelor, Master and PhD of Science levels to enhance the best skills available among physiotherapists, occupational health and safety technicians and ergonomists.

Due to the epochal changes introduced by “Industry 4.0”, it is getting harder to apply the varying approaches for biomechanical risk assessment of manual handling tasks used to prevent work-related musculoskeletal disorders (WMDs) considered within the International Standards for ergonomics. In fact, the innovative human–robot collaboration (HRC) systems are widening the number of work motor tasks that cannot be assessed. On the other hand, new sensor-based tools for biomechanical risk assessment could be used for both quantitative “direct instrumental evaluations” and “rating of standard methods”, allowing certain improvements over traditional methods. In this light, this Letter aims at detecting the need for revising the standards for human ergonomics and biomechanical risk assessment by analyzing the WMDs prevalence and incidence; additionally, the strengths and weaknesses of traditional methods listed within the International Standards for manual handling activities and the next challenges needed for their revision are considered. As a representative example, the discussion is referred to the lifting of heavy loads where the revision should include the use of sensor-based tools for biomechanical risk assessment during lifting performed with the use of exoskeletons, by more than one person (team lifting) and when the traditional methods cannot be applied. The wearability of sensing and feedback sensors in addition to human augmentation technologies allows for increasing workers’ awareness about possible risks and enhance the effectiveness and safety during the execution of in many manual handling activities.

The aim of this study was to analyze the effect of the level of amputation and various prosthetic devices on the muscle activation of the sound limb in people with unilateral transfemoral and transtibial amputation. We calculated the global coactivation of 12 muscles using the time-varying multimuscle coactivation function method in 37 subjects with unilateral transfemoral amputation (10, 16, and 11 with mechanical, electronic, and bionic prostheses, respectively), 11 subjects with transtibial amputation, and 22 healthy subjects representing the control group. The results highlighted that people with amputation had a global coactivation temporal profile similar to that of healthy subjects. However, amputation increased the level of the simultaneous activation of many muscles during the loading response and push-off phases of the gait cycle and decreased it in the midstance and swing subphases. This increased coactivation probably plays a role in prosthetic gait asymmetry and energy consumption. Furthermore, people with amputation and wearing electronic prosthesis showed lower global coactivation when compared with people wearing mechanical and bionic prostheses. These findings suggest that the global lower limb coactivation behavior can be a useful tool to analyze the motor control strategies adopted and the ability to adapt to the prosthetic device.

Background Subjects with transfemoral amputation (TFA) show an asymmetric gait pattern associated with a decreased ability to recover mechanical energy and an increased metabolic cost of walking. Research question This study aimed to identify the spatio-temporal and kinematic gait variables correlated with mechanical energy values in subjects with TFA and to observe the ability of the identified parameters to discriminate between TFA and controls according to the type of prosthesis. Methods The gait of 40 subjects with TFA was evaluated with a motion 3-D optoelectronic system. Nine subjects wore a mechanical prosthesis (TFAm), seventeen a C-Leg prosthesis (TFAc), and fourteen a Genium prosthesis (TFAg). Spatio-temporal and pelvic kinematic parameters were measured. Energy recovery was measured relative to the whole-body center of mass (CoM) kinematics as the fraction of mechanical energy recovered during each walking step (R-step). Correlation tests and multiple linear regression analyses were used to evaluate the correlation and association between kinematic and energy variables, respectively. Receiver operating characteristics curves were plotted to assess the ability of the correlated parameter to distinguish subjects with TFA from controls, and optimal cutoff point values were calculated according to the type of prosthesis. Results Among the spatio-temporal and kinematic parameters correlated to R-step, only pelvic obliquity of the prosthetic side was significantly associated with R-step. It showed an excellent ability to discriminate between TFA and controls. Furthermore, pelvic obliquity showed an excellent discriminative ability in identifying TFAm and TFAc and a good discriminative ability in identifying TFAg from controls. Significance Pelvic obliquity plays an important role in energy recovery during gait for subjects using prosthetics. This information might be exploited to monitor the adaptation of subjects with TFA to prosthetic devices, to lower the energetic cost of walking potentially, and to reduce the long-term risks of secondary physical complications in prosthetic users.

Work-related low-back disorders (WLBDs) can be caused by manual lifting tasks. Wearable devices used to monitor these tasks can be one possible way to assess the main risk factors for WLBDs. This study aims at analyzing the sensitivity of kinematic data to the risk level changes, and to define an instrument-based tool for risk classification by using kinematic data and artificial neural networks (ANNs). Twenty workers performed lifting tasks, designed by following the rules of the revised NIOSH lifting equation, with an increasing lifting index (LI). From the acquired kinematic data, we computed smoothness parameters together with kinetic, potential and mechanical energy. We used ANNs for mapping different set of features on LI levels to obtain an automatic risk estimation during these tasks. The results show that most of the calculated kinematic indexes are significantly affected by changes in LI and that all the lifting condition pairs can be correctly distinguished. Furthermore, using specific set of features, different topologies of ANNs can lead to a reliable classification of the biomechanical risk related to lifting tasks. In particular, the training sets and numbers of neurons in each hidden layer influence the ANNs performance, which is instead independent from the numbers of hidden layers. Reliable biomechanical risk estimation can be obtained by using training sets combining body and load kinematic features.

The aim of this work was to analyze the global coactivation (mechanism that regulates the simultaneous activity of antagonist muscles around the same joint) of the sound limb in people with unilateral trans-femoral and transtibial amputation in order to understand how the nervous system manages different levels of amputation and different types of prostheses. To achieve this aim, we calculated the global coactivation of 12 muscles using a time-varying multi-muscle co-activation function in 25 subjects with unilateral trans-femoral amputation (7, 12 and 6 with mechanical, electronic and bionic prosthesis respectively), in 7 subjects with trans-tibial amputation and in 20 healthy subjects representing the control group. The results highlight that, both trans-tibial and trans-femoral amputees show a characteristic double-peak shape as in healthy subjects although the second peak, in particular in subjects with trans-femoral amputation, appears to be slightly delayed with respect to the one that characterizes the control subjects. Furthermore, there is greater variability for both samples of amputees, with respect to the control subjects. On the other hand, TFA patients adopt similar strategies regardless of the kind of prosthesis. These results might indicate that the CNS has to manage, through the sound limb, a higher complexity due to double prosthetic joint of the amputated limb during the transfer to it of the body weight and all the control strategies that the patient adopts in response to the reorganization of the sensorimotor system as a consequence of the amputation. These findings suggest that the global lower limb coactivation behavior could be a useful measure of the motor control strategy, limb stiffness, postural stability in subjects with lower limb amputation.

The aims of this study were: (i) to determine kinematic, kinetic, and electromyographic characteristics of Junzuki karate punch in professional karate athletes; (ii) to identify biomechanical parameters that correlate with punch force and lead to a higher punching performance; (iii) to verify the presence of muscle co-activation in the upper limb, trunk, and lower limb muscles. Data were collected from nine experienced karatekas from the Accademia Italiana Karate e Arti Marziali during the execution of the specific punch. Mean punch forces (181.2 N) delivered to the target, the range of motion of both right and left knees (1.13 and 0.82 rad) and right elbow (1.49 rad) joints, and the angles at impact (knee: 0.81 and 0.91 rad; elbow: 1.19 rad) in the sagittal plane were computed. Furthermore, the trunk rotational angular acceleration (63.1 rad

Upper limb work-related musculoskeletal disorders have a 12-month prevalence ranging from 12 to 41% worldwide and can be partly caused by handling low loads at high frequency. The association between the myoelectric manifestation of elbow flexor muscle fatigue and occupational physical demand has never been investigated. It was hypothesized that an elbow flexor muscle fatigue index could be a valid risk indicator in handling low loads at high frequency. This study aims to measure the myoelectric manifestation of muscle fatigue of the three elbow flexor muscles during the execution of the work tasks in different risk conditions. Fifteen right-handed healthy adults were screened using a movement analysis laboratory consisting of optoelectronic, dynamometer and surface electromyographic systems. The main result indicates that the fatigue index calculated from the brachioradialis is sensitive to the interaction among risk classes, session and gender, and above all it is sensitive to the risk classes.

Background The above-knee amputation of a lower limb is a severe impairment that affects significantly the ability to walk; considering this, a complex adaptation strategy at the neuromuscular level is needed in order to be able to move safely with a prosthetic knee. In literature, it has been demonstrated that muscle activity during walking can be described via the activation of a small set of muscle synergies. The analysis of the composition and the time activation profiles of such synergies have been found to be a valid tool for the description of the motor control schemes in pathological subjects. Methods In this study, we used muscle synergy analysis techniques to characterize the differences in the modular motor control schemes between a population of 14 people with trans-femoral amputation and 12 healthy subjects walking at two different (slow and normal self-selected) speeds. Muscle synergies were extracted from a 12 lower-limb muscles sEMG recording via non-negative matrix factorization. Equivalence of the synergy vectors was quantified by a cross-validation procedure, while differences in terms of time activation coefficients were evaluated through the analysis of the activity in the different gait sub-phases. Results Four synergies were able to reconstruct the muscle activity in all subjects. The spatial component of the synergy vectors did not change in all the analysed populations, while differences were present in the activity during the sound limb’s stance phase. Main features of people with trans-femoral amputation’s muscle synergy recruitment are a prolonged activation of the module composed of calf muscles and an additional activity of the hamstrings’ module before and after the prosthetic heel strike. Conclusions Synergy-based results highlight how, although the complexity and the spatial organization of motor control schemes are the same found in healthy subjects, substantial differences are present in the synergies’ recruitment of people with trans femoral amputation. In particular, the most critical task during the gait cycle is the weight transfer from the sound limb to the prosthetic one. Future studies will integrate these results with the dynamics of movement, aiming to a complete neuro-mechanical characterization of people with trans-femoral amputation’s walking strategies that can be used to improve the rehabilitation therapies.

Aim of the study is to compare the most relevant protocols for the assessment of the rehabilitative path of patient with lower limb prosthesis.

The work reintegration following shoulder biomechanical overload illness is a multidimensional process, especially for those tasks requiring strength, movement control and arm dexterity. Currently different robotic devices used for upper limb rehabilitation are available on the market, but these devices are not based on activities focused on the work reintegration. Furthermore, the rehabilitation programmes aimed to the work reintegration are insufficiently focused on the recovery of the necessary skills for the re-employment.

Locomotion is a complex behaviour that requires the coordination of multiple body segments and muscle groups. Here we investigated how the weakness and spasticity in individuals with Hereditary Spastic Paraplegia (HSP) affect the coordination patterns of the lower limbs. We analysed kinematics and electromyographic (EMG) activity from 12 leg muscles in 21 persons with HSP and 20 control subjects at matched walking speeds. To assess the locomotor coordination, we examined the covariation between thigh, shank and foot elevation angles by means of principal component analysis and the modular organization of EMG patterns using the non-negative matrix factorization algorithm. The characteristic features of the HSP gait consisted in changes of the elevation angles covariation, the shape of the gait loop, reduced range of motion of the distal segments and significantly lower foot lift. The EMG factorization analysis revealed a comparable structure of the motor output between HSP and control groups, but significantly wider basic temporal patterns associated with muscles innervated from the sacral spinal segments in HSP. Overall, the applied methodology highlighted the impact of the corticospinal degeneration and spasticity on the coordination of distal limb segments and basic muscle modules associated with distal spinal segments.

Introduction Gait deficits are debilitating in people with Parkinson’s disease (PwPD), which inevitably deteriorate over time. Gait analysis is a valuable method to assess disease-specific gait patterns and their relationship with the clinical features and progression of the disease. Objectives Our study aimed to i) develop an automated diagnostic algorithm based on machine-learning techniques (artificial neural networks [ANNs]) to classify the gait deficits of PwPD according to disease progression in the Hoehn and Yahr (H-Y) staging system, and ii) identify a minimum set of gait classifiers. Methods We evaluated 76 PwPD (H-Y stage 1–4) and 67 healthy controls (HCs) by computerized gait analysis. We computed the time-distance parameters and the ranges of angular motion (RoMs) of the hip, knee, ankle, trunk, and pelvis. Principal component analysis was used to define a subset of features including all gait variables. An ANN approach was used to identify gait deficits according to the H-Y stage. Results We identified a combination of a small number of features that distinguished PwPDs from HCs (one combination of two features: knee and trunk rotation RoMs) and identified the gait patterns between different H-Y stages (two combinations of four features: walking speed and hip, knee, and ankle RoMs; walking speed and hip, knee, and trunk rotation RoMs). Conclusion The ANN approach enabled automated diagnosis of gait deficits in several symptomatic stages of Parkinson’s disease. These results will inspire future studies to test the utility of gait classifiers for the evaluation of treatments that could modify disease progression.

Repetitive and intensive exercises during robot-aided rehabilitation may expose patients to inappropriate and unsafe postures. The introduction of a sensory feedback can help the subject to perform the rehabilitation task with an ergonomic posture. In this work, the introduction of visual and vibrotactile feedback in a robotic platform for upper limb rehabilitation has been proposed to ensure ergonomic posture during rehabilitation. The two feedback modalities have been used to provide information about incorrect neck and trunk posture. Ten healthy subjects have been involved in this study. Each of them performed 3D reaching movements with the aid of the robotic platform in three different conditions, i.e. without feedback, with visual feedback and with vibrotactile feedback, and a comparative analysis has been carried out to evaluate feedback effectiveness, acceptance and performance. Experimental results show that in case of no feedback the subjects reach and maintain configurations that can lead to incorrect neck and trunk configurations and therefore, if repeated, to musculoskeletal disorders. Conversely, with visual or vibrotactile feedback, the subjects tend to correct inappropriate posture with both trunk and head during task performing.

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The design of patient-tailored rehabilitative protocols that feature a control strategy adaptable to the user's requirements represents one of the crucial factor that influences motor recovery mechanisms such as neuroplasticity. In this scenario, including the patient in the control loop can certaintly improve functional recovery in robot-aided rehabilitation. In this paper, a novel 3D bio-cooperative robotic platform based on subject status is developed and preliminary tested on 10 healthy subjects. A novel arm-weight support system is included into an operational robotic platform for 3D upper limb robot-aided rehabilitation. The robotic platform is capable of adapting therapy characteristics on the basis of specific patient needs thanks to biomechanical and physiological measurements, thus actively including the subject in the control loop. The level of arm-weight support and of the assistance provided by the end-effector robot are varied on the basis of muscular fatigue and of biomechanical indicators, respectively, providing the correct amount of assistance based on the assistance-as-nedeed approach. Evaluation tests of the proposed platform have been carried out on 10 healthy subjects performing 3D point-to-point tasks in two different conditions, i.e. with and without assistance-as-needed. The obtained results demonstrated that the proposed platform is adaptable to the real needs of the patients by also reducing the muscular fatigue without negatively influencing motion execution.

Background: In order to reduce the risk of work-related musculoskeletal disorders (WMSDs) several methods have been developed, accepted by the international literature and used in the workplace. The purpose of this systematic review was to describe recent implementations of wearable sensors for quantitative instrumental-based biomechanical risk assessments in prevention of WMSDs. Methods: Articles written until 7 May 2018 were selected from PubMed, Scopus, Google Scholar and Web of Science using specific keywords. Results: Instrumental approaches based on inertial measurement units and sEMG sensors have been used for direct evaluations to classify lifting tasks into low and high risk categories. Wearable sensors have also been used for direct instrumental evaluations in handling of low loads at high frequency activities by using the local myoelectric manifestation of muscle fatigue estimation. In the field of the rating of standard methods, on-body wireless sensors network-based approaches for real-time ergonomic assessment in industrial manufacturing have been proposed. Conclusions: Few studies foresee the use of wearable technologies for biomechanical risk assessment although the requirement to obtain increasingly quantitative evaluations, the recent miniaturization process and the need to follow a constantly evolving manual handling scenario is prompting their use.

Inappropriate work conditions represent the main cause for upper limb musculoskeletal disorders in many working professions. In this context, robotics and novel technologies might represent a new frontier of devices able to treat musculoskeletal disorders. This paper aims at proposing and preliminary testing a bio-cooperative robotic platform for upper limb rehabilitation composed of a redundant anthropomorphic manipulator, an active arm gravity support and a multimodal interface. With the proposed platform it is possible to extract performance and muscular fatigue indicators and accordingly adapt the level of assistance, provided by the anthropomorphic robot arm, and of arm support. Furthermore, it was verified if the use of the proposed platform allowed subjects to execute highly controlled movements while maintaining an ergonomic posture able to limit the trunk compensatory movements during reaching. A preliminary study on 8 healthy subjects was carried out and the Rapid Upper Limb Assessment test was adopted to assess the subject’s upperlimb posture during the rehabilitation task. The obtained results are encouraging for extending the study for rehabilitation in occupational contexts of patients with upper limb musculoskeletal pathologies.

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.

The aims of this study were: to identify surface electromyography (sEMG)-based indices of trunk muscles acquired during the execution of lifting tasks designed using the revised NIOSH lifting equation and featuring a progressively increasing lifting index (LI); to study changes of these indices in relation to the LI; to evaluate the relationship between the identified indices and forces ( F L 5 − S 1 ) and moments ( M L 5 − S 1 ) at the L5-S1 joint. sEMG, kinematic and kinetic data of 20 male workers were recorded in three conditions. We computed the average rectified value (ARV), root mean square (RMS) and maximum value (Max) of twelve trunk muscles and the muscle co-activation. We also estimated F L 5 − S 1 and M L 5 − S 1 . One-way repeated-measures ANOVA and post-hoc analysis showed that sEMG-based indices values increased with LI increment of 1 (LI = l, 2 and 3). sEMG and kinetic parameters were linearly correlated. Findings suggest a promising use of wearable sEMG sensors in developing instrumental-based risk assessment tools in either the laboratory or workplace. In fact, some indices discriminate the investigated risk levels and correlate with the variables that generate the damage.

The surface electromyographic (sEMG) data of 12 trunk muscles of 10 workers during the execution of lifting tasks using three lifting indices (LI) were recorded. The aims of this work were to: 1) identify the most sensitive trunk muscles with respect to changes in lifting conditions based on the selected sEMG features and 2) test whether machine-learning techniques (artificial neural networks) used for mapping time and frequency sEMG features on LI levels can improve the biomechanical risk assessment. The results show that the erector spinae longissimus is the trunk muscle for which every sEMG feature can significantly discriminate each pair of LI. Furthermore, only when using multi-domain features (time and frequency) a more complex artificial neural network can lead to an improved biomechanical risk classification related to lifting tasks.

International audience; Sedentary behavior is defined as sitting or lying with low energy expenditure. Humans in industrialized societies spend an increasing amount of time in sedentary behaviors every day. This has been associated with detrimental health outcomes. Despite a growing interest in the health effects of sedentary behavior at work, associations remain unclear, plausibly due to poor and diverse methods for assessing sedentary behavior. Thus, good practice guidance for researchers and practitioners on how to assess occupational sedentary behavior are needed. The aim of this paper is to provide a practical guidance for practitioners and researchers on how to assess occupational sedentary behavior. Ambulatory systems for use in field applications (wearables) are a promising approach for sedentary behavior assessment. Many different small-size consumer wearables, with long battery life and high data storage capacity are commercially available today. However, no stand-alone commercial system is able to assess sedentary behavior in accordance with its definition. The present paper offers decision support for practitioners and researchers in selecting wearables and data collection strategies for their purpose of study on sedentary behavior. Valid and reliable assessment of occupational sedentary behavior is currently not easy. Several aspects need to be considered in the decision process on how to assess sedentary behavior. There is a need for development of a cheap and easily useable wearable for assessment of occupational sedentary behavior by researchers and practitioners.

This study aims to evaluate trunk local stability in a group of patients with degenerative primary cerebellar ataxia and to correlate it with spatio-temporal parameters, clinical variables, and history of falls. Sixteen patients affected by degenerative cerebellar ataxia and 16 gender- and age-matched healthy adults were studied by means of an inertial sensor to measure trunk kinematics and spatio-temporal parameters during over-ground walking. Trunk local dynamic stability was quantified by the maximum Lyapunov exponent with short data series of the acceleration data. According to this index, low values indicate more stable trunk dynamics, while high values denote less stable trunk dynamics. Disease severity was assessed by means of International Cooperative Ataxia Rating Scale (ICARS) according to which higher values correspond to more severe disease, while lower values correspond to less severe disease.Patients displayed a higher short-term maximum Lyapunov exponent than controls in all three spatial planes, which was correlated with the age, onset of the disease, and history of falls. Furthermore, the maximum Lyapunov exponent was negatively correlated with ICARS balance, ICARS posture, and ICARS total scores.These findings indicate that trunk local stability during gait is lower in patients with cerebellar degenerative ataxia than that in healthy controls and that this may increase the risk of falls. Local dynamic stability of the trunk seems to be an important aspect in patients with ataxia and could be a useful tool in the evaluation of rehabilitative and pharmacological treatment outcomes.

Background The harmony of the human gait was recently found to be related to the golden ratio value (ϕ). The ratio between the duration of the stance and that of the swing phases of a gait cycle was in fact found to be close to ϕ, which implies that, because of the fractal property of autosimilarity of that number, the gait ratios stride/stance, stance/swing, swing/double support, were not significantly different from one another. We studied a group of patients with cerebellar ataxia to investigate how the differences between their gait ratios and the golden ratio are related to efficiency and stability of their gait, assessed by energy expenditure and stride-to-stride variability, respectively. Methods The gait of 28 patients who were affected by degenerative cerebellar ataxia and of 28 healthy controls was studied using a stereophotogrammetric system. The above mentioned gait ratios, the energy expenditure estimated using the pelvis reconstructed method and the gait variability in terms of the stride length were computed, and their relationships were analyzed. Matching procedures have also been used to avoid multicollinearity biases. Findings The gait ratio values of the patients were farther from the controls (and hence from ϕ), even in speed matched conditions ( P = 0.011, Cohen's D = 0.76), but not when the variability and energy expenditure were matched between the two groups (Cohen's D = 0.49). In patients with cerebellar ataxia, the farther the stance-swing ratio was from ϕ, the larger the total mechanical work ( R 2 adj = 0.64). Further, a significant positive correlation was observed between the difference of the gait ratio from the golden ratio and the severity of the disease ( R = 0.421, P = 0.026). Interpretation Harmony of gait appears to be a benchmark of physiological gait leading to physiological energy recovery and gait reliability. Neurorehabilitation of patients with ataxia might benefit from the restoration of harmony of their locomotor patterns.

Background Spastic gait is a key feature in patients with hereditary spastic paraparesis, but the gait characterization and the relationship between the gait impairment and clinical characteristics have not been investigated. Objectives To describe the gait patterns in hereditary spastic paraparesis and to identify subgroups of patients according to specific kinematic features of walking. Methods We evaluated fifty patients by computerized gait analysis and compared them to healthy participants. We computed time-distance parameters of walking and the range of angular motion at hip, knee, and ankle joints, and at the trunk and pelvis. Lower limb joint moments and muscle co-activation values were also evaluated. Results We identified three distinct subgroups of patients based on the range of motion values. Subgroup one was characterized by reduced hip, knee, and ankle joint range of motion. These patients were the most severely affected from a clinical standpoint, had the highest spasticity, and walked at the slowest speed. Subgroup three was characterized by an increased hip joint range of motion, but knee and ankle joint range of motion values close to control values. These patients were the most mildly affected and had the highest walking speed. Finally, subgroup two showed reduced knee and ankle joint range of motion, and hip range of motion values close to control values. Disease severity and gait speed in subgroup two were between those of subgroups one and three. Conclusions We identified three distinctive gait patterns in patients with hereditary spastic paraparesis that correlated robustly with clinical data. Distinguishing specific features in the gait patterns of these patients may help tailor pharmacological and rehabilitative treatments and may help evaluate therapeutic effects over time.

A compact description of coordinated muscle activity is provided by the factorization of electromyographic (EMG) signals. With the use of this approach, it has consistently been shown that multimuscle activity during human locomotion can be accounted for by four to five modules, each one comprised of a basic pattern timed at a different phase of gait cycle and the weighting coefficients of synergistic muscle activations. These modules are flexible, in so far as the timing of patterns and the amplitude of weightings can change as a function of gait speed and mode. Here we consider the adjustments of the locomotor modules related to unstable walking conditions. We compared three different conditions, i.e., locomotion of healthy subjects on slippery ground (SL) and on narrow beam (NB) and of cerebellar ataxic (CA) patients on normal ground. Motor modules were computed from the EMG signals of 12 muscles of the right lower limb using non-negative matrix factorization. The unstable gait of SL, NB, and CA showed significant changes compared with controls in the stride length, stride width, range of angular motion, and trunk oscillations. In most subjects of all three unstable conditions, >70% of the overall variation of EMG waveforms was accounted for by four modules that were characterized by a widening of muscle activity patterns. This suggests that the nervous system adopts the strategy of prolonging the duration of basic muscle activity patterns to cope with unstable conditions resulting from either slippery ground, reduced support surface, or pathology.

Several studies have demonstrated how cerebellar ataxia (CA) affects gait, resulting in deficits in multijoint coordination and stability. Nevertheless, how lesions of cerebellum influence the locomotor muscle pattern generation is still unclear. To better understand the effects of CA on locomotor output, here we investigated the idiosyncratic features of the spatiotemporal structure of leg muscle activity and impairments in the biomechanics of CA gait. To this end, we recorded the electromyographic (EMG) activity of 12 unilateral lower limb muscles and analyzed kinematic and kinetic parameters of 19 ataxic patients and 20 age-matched healthy subjects during overground walking. Neuromuscular control of gait in CA was characterized by a considerable widening of EMG bursts and significant temporal shifts in the center of activity due to overall enhanced muscle activation between late swing and mid-stance. Patients also demonstrated significant changes in the intersegmental coordination, an abnormal transient in the vertical ground reaction force and instability of limb loading at heel strike. The observed abnormalities in EMG patterns and foot loading correlated with the severity of pathology [International Cooperative Ataxia Rating Scale (ICARS), a clinical ataxia scale] and the changes in the biomechanical output. The findings provide new insights into the physiological role of cerebellum in optimizing the duration of muscle activity bursts and the control of appropriate foot loading during locomotion.

Objective A comprehensive treatment of Hereditary Spastic Paraplegia (HSP) should consider the specific pathophysiological changes in the spinal cord. Here we reported a detailed characterization of the spinal motoneuronal output in HSP during locomotion. Methods We recorded kinematics and electromyographic (EMG) activity of 12 leg muscles in 29 patients with pure forms of HSP and compared them with 30 controls while walking at matched speeds. We assessed the spinal locomotor output by evaluating EMG patterns and by mapping them onto the rostrocaudal location of the spinal motoneuron pools. Results The activity profiles of muscles innervated from the sacral segments were significantly wider in patients. Similarly, spinal maps revealed a tendency for spreading the main loci of activation, involving initially the sacral segments and, at more severe stages, the lumbar segments. Conclusions The degeneration of the corticospinal tract in HSP is associated with a widening of spinal locomotor output spreading from caudal to rostral segments. Significance The findings highlight pathophysiologically relevant differential changes in the spinal locomotor output in HSP related to the specific innervation of muscles in the spinal cord, and might be helpful for developing future therapeutic strategies and identifying physiological markers of the disease.