Enhancing Tai Chi Training System: Towards Group-Based and Hyper-Realistic Training Experiences.

In this article, we propose a lightweight and flexible enhanced Tai Chi training system composed of multiple standalone virtual reality (VR) devices. The system aims to enable a hyper-realistic multi-user action training platform at low cost by displaying real-time action guidance trajectories, providing real-world impossible visual effects and functions, and rapidly enhancing movement precision and communication interest for learners. We objectively evaluate participants' action quality at different levels of immersion, including traditional coach guidance (TCG), VR, and mixed reality (MR), along with subjective measures like motion sickness, quality of interaction, social meaning, presence/immersion to comprehensively explore the system's feasibility. The results indicate VR performs the best in training accuracy, but MR provides superior social experience and relatively high accuracy. Unlike TCG, MR offers hyper-realistic hand movement trajectories and Tai Chi social references. Compared with VR, MR provides more realistic avatar companions and a safer environment. In summary, MR balances accuracy and social experience.

A qualitative study exploring the ritual-like activity and therapeutic relationship between Pilates teachers and clients with persistent low back pain.

BACKGROUND AND PURPOSE: Pilates is a commonly recommended exercise modality for the management of persistent low back pain. Whilst guidelines recommend the use of exercise for low back pain, research suggests that no one exercise is superior, creating a question over the mechanism of effect. The patient-practitioner relationship may be important in managing low back pain; however, the relationship between Pilates teachers and clients is not well understood. The purpose of this study was to identify the components of the relationship between Pilates teachers and clients with persistent low back pain, explore key influences on the relationship, and ascertain the nature of the relationship. METHOD: We conducted a qualitative, ethnographically-informed study at eight sites in the South of England, observing 24 Pilates sessions and interviewing 9 Pilates teachers and 10 clients with persistent low back pain. Fieldnotes and interview transcripts were analysed thematically. RESULTS: The findings demonstrate a complex, multi-faceted interaction that occurs during Pilates sessions, grounded within certain health perceptions, and predicated on expectations of individuality, choice and expertise. A key finding reveals the perceived importance of mastery of prescribed movements with control and precision, in which clients particularly value the authority of the teacher in a directive learning environment. CONCLUSION: We contend that the role of the Pilates teacher in this study facilitated the alleviation of clients' distress through the application of ritual-like Pilates activity. We conclude that the relationship between Pilates teachers and clients with persistent low back pain may be considered a therapeutic relationship.

Development and pilot of equine facilitated physical therapy outcome measure tool for chronic low back pain patients.

Equine Facilitated Physical Therapy (EFPT) lacks consistent documentation due to being an unconventional physical therapy treatment to chronic low back pain patients (LBP) and lacking rehabilitation outcome measure tools for a stable (equestrian) environment. The objectives were to develop an online evaluation tool as well as to define inter- and intra-rater reliability to validate the outcome measurement tool "Evaluation of maintaining sitting position (on a horse) and walking (short distances)" designed for LBP patients in EFPT". A total of 48 movement related functions (n = 48), were derived from the International Classification of Functioning (ICF) and organized to an online evaluation tool. Depending on the state of validation two to six (2-6) raters scored randomized patient (n = 22) video material, recorded during a 12-week EFPT intervention, with the designed tool. Inter-rater agreement level between the experts reached good (α = 87) reliability for the scoring of the items and calculated per patient excellent (α = 100). Intra-rater reliability reached good (α = 87) and per patient good (α = 80) repeatability. For the healthy adults the reliability between raters reached acceptable (α = 72) levels and per rated excellent (α = 100). The developed assessment tool was found satisfactory to fulfil the requirement for the therapeutic practice. With the use of the tool physical therapist may detect postural changes for LBP patients as outcome report in EFPT. The tool may be used to identify treatment progress and to help design home exercises. The created tool will help to collect similar outcome measures from LBP patients in EFPT and to validate the treatment within industry.

Joint knee loads during squat with constant or variable resistance in males. A clinical trial.

BACKGROUND: In the squat movement, the use of constant resistance (CR) generates greater compression and shear forces close to 90° of knee flexion, increasing joint overload. However, when used variable resistance (VR) there is no consensus about the effect of knee joint load. The aim of this study was to compare knee torques using constant or variable resistance during the squat exercise. METHODS: Twenty-one healthy male subjects (mean age, 24 [SD, 3] years; height, 1.76 [SD, 0.04] m), who practice squats during strength training routine. Were simultaneously record data from the platform force and tridimensional kinematic to obtain torques around knee. 15 repetitions were performed up to maximum knee flexion with the use of variable (RV) or constant (CR) resistance in a single session. RESULTS: Significant differences regarding the angles only in the sagittal plane at the end of the ascending phase of the squat, with less knee extension in the VR condition. In the sagittal and frontal planes, lower values of extensor and abductor torque were found in the VR condition at the angles of greater knee flexion. CONCLUSION: The use of variable resistance compared to constant resistance seems to be an alternative to be considered when the objective is to minimize the internal loads on the knee joint in exercises such as the squat in amplitudes of greater flexion. This study indicated that VR helps subjects who are learning the squat movement, enabling the application of this knowledge in physical therapy or physical training clinics.

Brain-wide neural activity underlying memory-guided movement.

Behavior relies on activity in structured neural circuits that are distributed across the brain, but most experiments probe neurons in a single area at a time. Using multiple Neuropixels probes, we recorded from multi-regional loops connected to the anterior lateral motor cortex (ALM), a circuit node mediating memory-guided directional licking. Neurons encoding sensory stimuli, choices, and actions were distributed across the brain. However, choice coding was concentrated in the ALM and subcortical areas receiving input from the ALM in an ALM-dependent manner. Diverse orofacial movements were encoded in the hindbrain; midbrain; and, to a lesser extent, forebrain. Choice signals were first detected in the ALM and the midbrain, followed by the thalamus and other brain areas. At movement initiation, choice-selective activity collapsed across the brain, followed by new activity patterns driving specific actions. Our experiments provide the foundation for neural circuit models of decision-making and movement initiation.

How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Imagery.

This study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation states. Additionally, this work presents a system for obstacle detection based on image processing. The implemented system constitutes a complementary part of the interface. The main contributions of this work include the proposal of a modified 10-20-electrode setup suitable for motor imagery classification, the design of two convolutional neural network (CNNs) models employed to classify signals acquired from sixteen EEG channels, and the implementation of an obstacle detection system based on computer vision integrated with a brain-machine interface. The models developed in this study achieved an accuracy of 83% in classifying EEG signals. The resulting classification outcomes were subsequently utilized to control the movement of a mobile robot. Experimental trials conducted on a designated test track demonstrated real-time control of the robot. The findings indicate the feasibility of integration of the obstacle detection system for collision avoidance with the classification of motor imagery for the purpose of brain-machine interface control of vehicles. The elaborated solution could help paralyzed patients to safely control a wheelchair through EEG and effectively prevent unintended vehicle movements.

Action observation with motor simulation improves reactive stepping responses following strong backward balance perturbations in healthy young individuals.

BACKGROUND AND OBJECTIVE: Adequate reactive steps are critical for preventing falls following balance perturbations. Perturbation-based balance training was shown to improve reactive stepping in various clinical populations, but its delivery is labor-intensive and generally uses expensive equipment. Action observation of reactive steps with either motor imagery (AOMI) or motor simulation (AOMS) are potential alternative training modalities. We here aimed to study their effects on reactive stepping performance. METHODS: Sixty healthy young subjects were subjected to forward platform translations that elicited backward reactive steps. The AOMI group (n = 20) was tested after AOMI of an actor's reactive steps, while the AOMS group (n = 20) additionally stepped along with the actor. The control group (n = 20) was tested without any prior observation. Our primary outcome was the step quality of the first trial response, as this best represents a real-life loss-of-balance. Step quality was quantified as the leg angle with respect to the vertical at stepping-foot contact. We also studied single step success rates and reactive step quality across repeated trials. RESULTS: Reactive step quality was significantly better in the AOMI and AOMS groups than in the control group, which differences coincided with a twofold higher single step success rate. Reactive step quality improved upon repeated trials in all groups, yet the AOMS group needed the fewest repetitions to reach plateau performance. SIGNIFICANCE: The present results demonstrate that both AOMI and AOMS improved first and repeated trial reactive stepping performance. These findings point at the potential applicability of these concepts for home-based reactive balance training, for instance in serious games, with overt movements (AOMS) possibly having some benefits over mental imaginations (AOMI). Whether similar beneficial effects also emerge in the target populations of balance-impaired individuals remains to be investigated.

Beta bursts question the ruling power for brain-computer interfaces.

Objective: Current efforts to build reliable brain-computer interfaces (BCI) span multiple axes from hardware, to software, to more sophisticated experimental protocols, and personalized approaches. However, despite these abundant efforts, there is still room for significant improvement. We argue that a rather overlooked direction lies in linking BCI protocols with recent advances in fundamental neuroscience.Approach: In light of these advances, and particularly the characterization of the burst-like nature of beta frequency band activity and the diversity of beta bursts, we revisit the role of beta activity in 'left vs. right hand' motor imagery (MI) tasks. Current decoding approaches for such tasks take advantage of the fact that MI generates time-locked changes in induced power in the sensorimotor cortex and rely on band-passed power changes in single or multiple channels. Although little is known about the dynamics of beta burst activity during MI, we hypothesized that beta bursts should be modulated in a way analogous to their activity during performance of real upper limb movements.Main results and Significance: We show that classification features based on patterns of beta burst modulations yield decoding results that are equivalent to or better than typically used beta power across multiple open electroencephalography datasets, thus providing insights into the specificity of these bio-markers.

Effects of Manual Therapy on Parkinson's Gait: A Systematic Review.

Manual therapy (MT) is commonly used in rehabilitation to deal with motor impairments in Parkinson's disease (PD). However, is MT an efficient method to improve gait in PD? To answer the question, a systematic review of clinical controlled trials was conducted. Estimates of effect sizes (reported as standard mean difference (SMD)) with their respective 95% confidence interval (95% CI) were reported for each outcome when sufficient data were available. If data were lacking, p values were reported. The PEDro scale was used for the quality assessment. Three studies were included in the review. MT improved Dynamic Gait Index (SMD = 1.47; 95% CI: 0.62, 2.32; PEDro score: 5/10, moderate level of evidence). MT also improved gait performances in terms of stride length, velocity of arm movements, linear velocities of the shoulder and the hip (p < 0.05; PEDro score: 2/10, limited level of evidence). There was no significant difference between groups after MT for any joint's range of motion during gait (p > 0.05; PEDro score: 6/10, moderate level of evidence). There is no strong level of evidence supporting the beneficial effect of MT to improve gait in PD. Further randomized controlled trials are needed to understand the impact of MT on gait in PD.

Differences in motor imagery abilities in active and sedentary individuals: new insights from backward-walking imagination.

Evidence has shown that imagining a complex action, like backward-walking, helps improve the execution of the gesture. Despite this, studies in sport psychology have provided heterogeneous results on the use of motor imagery (MI) to improve performance. We aimed to fill this gap by analyzing how sport experience influences backward-walking MI processes in a sample of young women (n = 41, mean age = 21 ± 2.2) divided into Active and Sedentary. All participants were allocated to two randomized mental chronometric tasks, in which they had first to imagine and then execute forward-walking (FW) and backward-walking (BW). The Isochrony Efficiency measured the difference between imagination and execution times in both conditions (FW and BW). Moreover, we analyzed the ability to vividly imagine FW and BW within various perspectives in both groups through the Vividness of Movement Imagery Questionnaire (VMIQ-2). Findings showed that active individuals performed better in the BW imagery task when compared to sedentary ones (F1,39 = 4.98; p = 0.03*), while there were no differences between groups in the FW imagery task (F1,39 = .10; p = 0.75). Further, VMIQ-2 had evidenced that the ability to imagine backward is influenced by perspective used. Specifically, the use of internal visual imagery (IVI) led to worse Isochrony Efficiency (t32,25 = 2.16; p = 0.04*), while the use of kinesthetic imagery (KIN) led to better Isochrony Efficiency (t32,25 = - 2.34; p = 0.03*). These results suggest a close relation between motor experience and complex motor imagery processes and open new insights for studying these mental processes.

Motor cortex activation during visuomotor transformations: evoked potentials during overt and imagined movements.

Despite the prevalence of visuomotor transformations in our motor skills, their mechanisms remain incompletely understood, especially when imagery actions are considered such as mentally picking up a cup or pressing a button. Here, we used a stimulus-response task to directly compare the visuomotor transformation underlying overt and imagined button presses. Electroencephalographic activity was recorded while participants responded to highlights of the target button while ignoring the second, non-target button. Movement-related potentials (MRPs) and event-related desynchronization occurred for both overt movements and motor imagery (MI), with responses present even for non-target stimuli. Consistent with the activity accumulation model where visual stimuli are evaluated and transformed into the eventual motor response, the timing of MRPs matched the response time on individual trials. Activity-accumulation patterns were observed for MI, as well. Yet, unlike overt movements, MI-related MRPs were not lateralized, which appears to be a neural marker for the distinction between generating a mental image and transforming it into an overt action. Top-down response strategies governing this hemispheric specificity should be accounted for in future research on MI, including basic studies and medical practice.

Signature methods for brain-computer interfaces.

Brain-computer interfaces (BCIs) allow direct communication between one's central nervous system and a computer without any muscle movement hence by-passing the peripheral nervous system. They can restore disabled people's ability to interact with their environment, e.g. communication and wheelchair control. However, to this day their performance is still hindered by the non-stationarity of electroencephalography (EEG) signals, as well as their susceptibility to noise from the users' environment and from their own physiological activity. Moreover, a non-negligible amount of users struggle to use BCI systems based on motor imagery. In this paper, a new method based on the path signature is introduced to tackle this problem by using features which are different from the usual power-based ones. The path signature is a series of iterated integrals computed from a multidimensional path. It is invariant under translation and time reparametrization, which makes it a robust feature for multichannel EEG time series. The performance can be further boosted by combining the path signature with the gold standard Riemannian classifier in the BCI field exploiting the geometric structure of symmetric positive definite (SPD) matrices. The results obtained on publicly available datasets show that the signature method is more robust to inter-user variability than classical ones, especially on noisy and low-quality data. Hence, this study paves the way towards the use of mathematical tools that until now have been neglected, in order to tackle the EEG-based BCI variability issue. It also sheds light on the lead-lag relationship captured by path signature which seems relevant to assess the underlying neural mechanisms.

A wearable inertial system to evaluate Tai Chi training motor effects in patients with Parkinson's disease.

Physical therapy is strongly recommended for patients with neurological disorders. Tai Chi-based treatments seem to improve physical functions like gait speed and balance. However, assessments after treatment rely on semi-quantitative clinical scales affected by subjectivity with controversial results. This study aims at investigating whether Tai Chi could be a valid alternative to traditional physiotherapy rehabilitation. We propose a wearable system composed of two inertial devices able to objectively measure the effect of the rehabilitation treatment on the range of movement of the trunk. Seventeen patients with Parkinson's Disease (PD) were recruited and assessed. They have been randomly divided into two groups: group 1 followed a Tai Chi-based treatment, while group 2 underwent a traditional physiotherapy rehabilitation. The two groups have been assessed before (t0) and after the treatment (t1). No statistical differences have been found in the relative range of motion between the upper and lower sensors between the two groups at the baseline. Both treatments resulted in a significant improvement in the trunk range of movement (on the right side). Notably, the improvement in the effect size of the treatment was greater in group 1 than in group 2. In fact, even if both the groups benefited from their treatment group 1 gained larger mobility of the trunk if compared to group 2. Interestingly, no differences have been accounted adopting the traditional UPDRS III for motor symptoms of PD, strengthening the idea that objective measurement coming from wearable biomedical sensors could detect information otherwise neglected by traditional clinical tools.Clinical Relevance- This study preliminary confirms that beneficial motor effects after a Tai Chi rehabilitation program are comparable and quite better than after traditional physiotherapy, promoting Tai Chi as a valid alternative treatment for PD patients.

Towards user-centric BCI design: Markov chain-based user assessment for mental imagery EEG-BCIs.

Objective.While electroencephalography (EEG)-based brain-computer interfaces (BCIs) have many potential clinical applications, their use is impeded by poor performance for many users. To improve BCI performance, either via enhanced signal processing or user training, it is critical to understand and describe each user's ability to perform mental control tasks and produce discernible EEG patterns. While classification accuracy has predominantly been used to assess user performance, limitations and criticisms of this approach have emerged, thus prompting the need to develop novel user assessment approaches with greater descriptive capability. Here, we propose a combination of unsupervised clustering and Markov chain models to assess and describe user skill.Approach.Using unsupervisedK-means clustering, we segmented the EEG signal space into regions representing pattern states that users could produce. A user's movement through these pattern states while performing different tasks was modeled using Markov chains. Finally, using the steady-state distributions and entropy rates of the Markov chains, we proposed two metricstaskDistinctandrelativeTaskInconsistencyto assess, respectively, a user's ability to (i) produce distinct task-specific patterns for each mental task and (ii) maintain consistent patterns during individual tasks.Main results.Analysis of data from 14 adolescents using a three-class BCI revealed significant correlations between thetaskDistinctandrelativeTaskInconsistencymetrics and classification F1 score. Moreover, analysis of the pattern states and Markov chain models yielded descriptive information regarding user performance not immediately apparent from classification accuracy.Significance.Our proposed user assessment method can be used in concert with classifier-based analysis to further understand the extent to which users produce task-specific, time-evolving EEG patterns. In turn, this information could be used to enhance user training or classifier design.

Usefulness of thalamic beta activity for closed-loop therapy in essential tremor.

A partial loss of effectiveness of deep brain stimulation of the ventral intermediate nucleus of the thalamus (VIM) has been reported in some patients with essential tremor (ET), possibly due to habituation to permanent stimulation. This study focused on the evolution of VIM local-field potentials (LFPs) data over time to assess the long-term feasibility of closed-loop therapy based on thalamic activity. We performed recordings of thalamic LFPs in 10 patients with severe ET using the ACTIVA™ PC + S (Medtronic plc.) allowing both recordings and stimulation in the same region. Particular attention was paid to describing the evolution of LFPs over time from 3 to 24 months after surgery when the stimulation was Off. We demonstrated a significant decrease in high-beta LFPs amplitude during movements inducing tremor in comparison to the rest condition 3 months after surgery (1.91 ± 0.89 at rest vs. 1.27 ± 1.37 µV2/Hz during posture/action for N = 8/10 patients; p = 0.010), 12 months after surgery (2.92 ± 1.75 at rest vs. 2.12 ± 1.78 µV2/Hz during posture/action for N = 7/10 patients; p = 0.014) and 24 months after surgery (2.32 ± 0.35 at rest vs 0.75 ± 0.78 µV2/Hz during posture/action for 4/6 patients; p = 0.017). Among the patients who exhibited a significant decrease of high-beta LFP amplitude when stimulation was Off, this phenomenon was observed at least twice during the follow-up. Although the extent of this decrease in high-beta LFPs amplitude during movements inducing tremor may vary over time, this thalamic biomarker of movement could potentially be usable for closed-loop therapy in the long term.

Deep temporal networks for EEG-based motor imagery recognition.

The electroencephalogram (EEG) based motor imagery (MI) signal classification, also known as motion recognition, is a highly popular area of research due to its applications in robotics, gaming, and medical fields. However, the problem is ill-posed as these signals are non-stationary and noisy. Recently, a lot of efforts have been made to improve MI signal classification using a combination of signal decomposition and machine learning techniques but they fail to perform adequately on large multi-class datasets. Previously, researchers have implemented long short-term memory (LSTM), which is capable of learning the time-series information, on the MI-EEG dataset for motion recognition. However, it can not model very long-term dependencies present in the motion recognition data. With the advent of transformer networks in natural language processing (NLP), the long-term dependency issue has been widely addressed. Motivated by the success of transformer algorithms, in this article, we propose a transformer-based deep learning neural network architecture that performs motion recognition on the raw BCI competition III IVa and IV 2a datasets. The validation results show that the proposed method achieves superior performance than the existing state-of-the-art methods. The proposed method produces classification accuracy of 99.7% and 84% on the binary class and the multi-class datasets, respectively. Further, the performance of the proposed transformer-based model is also compared with LSTM.

Robot-Inspired Human Impedance Control Through Functional Electrical Stimulation.

Functional Electrical Stimulation is an effective tool to foster rehabilitation of neurological patients suffering from impaired motor functions. It can also serve as an assistive device to compensate for compromised motor functions in the chronic phase occurring after a disease or trauma. In all cases, the dominant paradigm in FES applications is that of aiding specialized, task-specific movements, such as reaching or grasping. Usually this is achieved by targeting specific muscle groups which are associated to the targeted motion by experts. A general purpose, FES-based control theory capable of enabling neurological patients to achieve a wide range of positional goals in their peri-personal space is still missing. In this paper, we present an early analysis of the performance achievable through a muscular impedance control loop employing FES to actuate force and movement. The control is evaluated in a test where the user's upper limb is moved by means of an exonerve to a series of target positions on a plane without providing visual feedback nor requiring volitional effort. The results allow to characterize the performance of such a setup over time and to assess how well can it generalize over different target positions in the user's peri-personal space. The current study population also allows to evaluate the effects of user's experience with FES systems on the overall performance during the test. The results indicate that the proposed control loop can generalize well over different arm poses.

Thalamic Foxp2 regulates output connectivity and sensory-motor impairments in a model of Huntington's Disease.

BACKGROUND: Huntington's Disease (HD) is a disorder that affects body movements. Altered glutamatergic innervation of the striatum is a major hallmark of the disease. Approximately 30% of those glutamatergic inputs come from thalamic nuclei. Foxp2 is a transcription factor involved in cell differentiation and reported low in patients with HD. However, the role of the Foxp2 in the thalamus in HD remains unexplored. METHODS: We used two different mouse models of HD, the R6/1 and the HdhQ111 mice, to demonstrate a consistent thalamic Foxp2 reduction in the context of HD. We used in vivo electrophysiological recordings, microdialysis in behaving mice and rabies virus-based monosynaptic tracing to study thalamo-striatal and thalamo-cortical synaptic connectivity in R6/1 mice. Micro-structural synaptic plasticity was also evaluated in the striatum and cortex of R6/1 mice. We over-expressed Foxp2 in the thalamus of R6/1 mice or reduced Foxp2 in the thalamus of wild type mice to evaluate its role in sensory and motor skills deficiencies, as well as thalamo-striatal and thalamo-cortical connectivity in such mouse models. RESULTS: Here, we demonstrate in a HD mouse model a clear and early thalamo-striatal aberrant connectivity associated with a reduction of thalamic Foxp2 levels. Recovering thalamic Foxp2 levels in the mouse rescued motor coordination and sensory skills concomitant with an amelioration of neuropathological features and with a repair of the structural and functional connectivity through a restoration of neurotransmitter release. In addition, reduction of thalamic Foxp2 levels in wild type mice induced HD-like phenotypes. CONCLUSIONS: In conclusion, we show that a novel identified thalamic Foxp2 dysregulation alters basal ganglia circuits implicated in the pathophysiology of HD.

A systematic model to identify and reduce work-related musculoskeletal disorders in firefighters, and improve their function.

INTRODUCTION: Firefighting is a high-risk job with a high prevalence of work-related musculoskeletal disorders (WMSDs). The aim of his study was to determine the prevalence of WMSDs, estimate the likelihood of subsequent disorders, and investigate the effect of NASM-based training protocol on firefighters function. METHOD: First, prevalence and region of WMSDs in all 524 male Isfahan firefighters were determined by Medical-history-questionnaire. Then, functional movement screen (FMS) separated firefighters to the 2-dimension FMS score (FMSCS≤14 or FMSCS>14) to show at risk firefighters. Finally, 40 Participants with both FMSCS≤14 and common WMSDs randomly assigned to either an intervention (IG) (n = 20) or control (CG) (n = 20) group. The IG received NASM-based training, while the CG engaged in daily activities. Outcomes included movement efficiency during landing error scoring system-real time, Y balance, single-leg squat, and deep squat, which were assessed in pretest and posttest. RESULTS: The prevalence of disorders was 52.1%, which lower limb, back, upper limb, and neck were the highest prevalence respectively. Only lower limb and back disorders could identify individuals at disorder risk with a likelihood of 89% and 71%, sequentially. Also, movement performance significantly improved in all functional tests in IG relative to CG. CONCLUSIONS: Considering high disorder rate in firefighters, the value of our study lies in alleging a systematic model periodically to reduce WMSDs and risk of subsequent disorders. Not only our model determined the prevalence of WMSDs, but it also identified those who are at risk. In addition, our model represents exercise therapy as a solution.

Evaluation of arthrokinematics and posterior soft tissues of the ankle during ankle dorsiflexion using ultrasound.

BACKGROUND: Arthrokinematics (caudal and posterior movements of the talus) and posterior soft tissues of the ankle during ankle dorsiflexion have not been objectively evaluated in detail. This study aimed to investigate the characteristics of arthrokinematics and posterior soft tissues of the ankle during ankle dorsiflexion using ultrasound. METHODS: Thirteen healthy adults participated in the study. Participants whose passive dorsiflexion range of motion (ROM) of the ankle joint was <35° were classified as the restricted group (n = 6), and participants whose passive ankle dorsiflexion ROM was ≥35° were classified as the control group (n = 7). Passive ankle dorsiflexion was performed to measure the ankle arthrokinematics. Strain elastography was performed to measure the elasticity of the flexor hallucis longus (FHL) and Kager's fat pad (KFP) at each dorsiflexion angle. RESULTS: A significant difference in the posterior movement of the talus at the ankle dorsiflexion of 30° was observed between the two groups (P = 0.04). The elasticity of the restricted group was increased at all angles in both FHL and KFP (P < 0.05). CONCLUSION: This study showed that it is possible to objectively evaluate the direction of ankle arthrokinematics and posterior ankle soft-tissue restrictions using ultrasound.