Quasi-experimental pilot study to improve mobility and balance in recurrently falling nursing home residents by voluntary non-targeted side-stepping exercise intervention.

BACKGROUND: Side-stepping is a potential exercise program to reduce fall risk in community-dwelling adults in their seventies, but it has never been tested in nursing home residents. This was a pilot quasi-experimental study to examine the feasibility and potential mobility and balance benefits of an intervention based on voluntary non-targeted side-stepping exercises in nursing home residents who fall recurrently. METHODS: Twenty-two participants were recruited and non-randomly assigned to an intervention group ([Formula: see text]11, side-stepping exercises, STEP) participating in an 8-week protocol and to a control group ([Formula: see text]11, usual physiotherapy care, CTRL). They were clinically assessed at 4-time points: baseline, after 4 and 8 weeks, and after a 4-week follow-up period (usual physiotherapy care). Statistical differences between time points were assessed with a Friedman repeated measures ANOVA on ranks or a one-way repeated measures ANOVA. RESULTS: Compared to baseline, significant benefits were observed in the STEP group at 8 weeks for the Timed Up and Go ([Formula: see text]0.020) and 6-minute walking test ([Formula: see text]0.001) as well as for the Berg Balance Scale ([Formula: see text]0.041) and Mini motor test ([Formula: see text]0.026). At follow-up, the Tinetti Performance Oriented Mobility Assessment and Berg Balance Scale significantly worsened in the STEP group ([Formula: see text]0.009 and [Formula: see text]0.001, respectively). No significant differences were found between the groups at the same time points. CONCLUSIONS: Our intervention was feasible and improved mobility and balance after almost 8 weeks. Studies with larger samples and randomized control trials are needed to consolidate our preliminary observations and confirm the deterioration of some tests when side-stepping exercises are discontinued. TRIAL REGISTRATION: Identifier: ISRCTN13584053. Retrospectively registered 01/09/2022.

Head Pitch Angular Velocity Discriminates (Sub-)Acute Neck Pain Patients and Controls Assessed with the DidRen Laser Test.

Understanding neck pain is an important societal issue. Kinematic data from sensors may help to gain insight into the pathophysiological mechanisms associated with neck pain through a quantitative sensorimotor assessment of one patient. The objective of this study was to evaluate the potential usefulness of artificial intelligence with several machine learning (ML) algorithms in assessing neck sensorimotor performance. Angular velocity and acceleration measured by an inertial sensor placed on the forehead during the DidRen laser test in thirty-eight acute and subacute non-specific neck pain (ANSP) patients were compared to forty-two healthy control participants (HCP). Seven supervised ML algorithms were chosen for the predictions. The most informative kinematic features were computed using Sequential Feature Selection methods. The best performing algorithm is the Linear Support Vector Machine with an accuracy of 82% and Area Under Curve of 84%. The best discriminative kinematic feature between ANSP patients and HCP is the first quartile of head pitch angular velocity. This study has shown that supervised ML algorithms could be used to classify ANSP patients and identify discriminatory kinematic features potentially useful for clinicians in the assessment and monitoring of the neck sensorimotor performance in ANSP patients.

Wearable Sensors Applied in Movement Analysis.

Recent advances in the miniaturization of electronics have resulted in sensors whose sizes and weights are such that they can be attached to living systems without interfering with their natural movements and behaviors [...].

High Specificity of Single Inertial Sensor-Supplemented Timed Up and Go Test for Assessing Fall Risk in Elderly Nursing Home Residents.

The Timed Up and Go test (TUG) is commonly used to estimate the fall risk in the elderly. Several ways to improve the predictive accuracy of TUG (cameras, multiple sensors, other clinical tests) have already been proposed. Here, we added a single wearable inertial measurement unit (IMU) to capture the residents' body center-of-mass kinematics in view of improving TUG's predictive accuracy. The aim is to find out which kinematic variables and residents' characteristics are relevant for distinguishing faller from non-faller patients. Data were collected in 73 nursing home residents with the IMU placed on the lower back. Acceleration and angular velocity time series were analyzed during different subtasks of the TUG. Multiple logistic regressions showed that total time required, maximum angular velocity at the first half-turn, gender, and use of a walking aid were the parameters leading to the best predictive abilities of fall risk. The predictive accuracy of the proposed new test, called i + TUG, reached a value of 74.0%, with a specificity of 95.9% and a sensitivity of 29.2%. By adding a single wearable IMU to TUG, an accurate and highly specific test is therefore obtained. This method is quick, easy to perform and inexpensive. We recommend to integrate it into daily clinical practice in nursing homes.

Machine Learning Identifies Chronic Low Back Pain Patients from an Instrumented Trunk Bending and Return Test.

Nowadays, the better assessment of low back pain (LBP) is an important challenge, as it is the leading musculoskeletal condition worldwide in terms of years of disability. The objective of this study was to evaluate the relevance of various machine learning (ML) algorithms and Sample Entropy (SampEn), which assesses the complexity of motion variability in identifying the condition of low back pain. Twenty chronic low-back pain (CLBP) patients and 20 healthy non-LBP participants performed 1-min repetitive bending (flexion) and return (extension) trunk movements. Analysis was performed using the time series recorded by three inertial sensors attached to the participants. It was found that SampEn was significantly lower in CLBP patients, indicating a loss of movement complexity due to LBP. Gaussian Naive Bayes ML proved to be the best of the various tested algorithms, achieving 79% accuracy in identifying CLBP patients. Angular velocity of flexion movement was the most discriminative feature in the ML analysis. This study demonstrated that: supervised ML and a complexity assessment of trunk movement variability are useful in the identification of CLBP condition, and that simple kinematic indicators are sensitive to this condition. Therefore, ML could be progressively adopted by clinicians in the assessment of CLBP patients.

Metabolic Energy Expenditure and Accelerometer-Determined Physical Activity Levels in Post-Stroke Hemiparetic Patients.

BACKGROUND: Assessment of metabolic energy expenditure in post-stroke patients using accelerometers is clinically important. However, understanding of the best placement of accelerometers on the body and methods for calculating activity counts are limited. METHODS: Thirty hemiparetic post-stroke patients participated in this cross-sectional study. Four triaxial accelerometers were attached to the hemiplegic and contralateral sides of the waist and ankles during various activities: lying, sitting, standing, stepping in place, and walking on a treadmill (1-5 kmh-1). Activity counts and metabolic energy expenditure of the patients were recorded simultaneously. Simple linear regression analyses were performed between the activity counts and energy expenditure. Activities were classified according to their intensity, using the definition of energetic sedentary behavior of post-stroke patients and a low fitness level group. RESULTS: The best estimate of energy expenditure was obtained when the accelerometer was worn on the contralateral ankle and the activity counts was calculated using the vertical and anteroposterior axes (R2=0.812). Six classes of activity intensity (sedentary: ≤1.5 METs, very light: 1.51-1.79, light: 1.80-2.59, moderate: 2.60-3.39, hard: 3.40-4.39, and very hard: ≥4.40) and corresponding activity counts cut-off points are presented. CONCLUSION: A triaxial accelerometer worn on the contralateral ankle and a method of calculating activity counts that includes at least the vertical and anteroposterior axes are recommended for estimating metabolic energy expenditure in post-stroke patients. The new activity counts cut-off points provide a significant advance in the interpretation of post-stroke monitoring in patients outside the hospital or rehabilitation center.

Sensorimotor performance in acute-subacute non-specific neck pain: a non-randomized prospective clinical trial with intervention.

BACKGROUND: The assessment of cervical spine kinematic axial rotation performance is of great importance in the context of the study of neck sensorimotor control. However, studies addressing the influence of the level of provocation of spinal pain and the potential benefit of passive manual therapy mobilizations in patients with acute-subacute non-specific neck pain are lacking. METHODS: A non-randomized prospective clinical trial with an intervention design was conducted. We investigated: (1) the test-retest reliability of kinematic variables during a fast axial head rotation task standardized with the DidRen laser test device in 42 Healthy pain-free Control Participants (HCP) (24.3 years ±6.8); (2) the differences in kinematic variables between HCP and 38 patients with Acute-subacute Non-Specific neck Pain (ANSP) assigned to two different groups according to whether their pain was localized in the upper or lower spine (46.2 years ±16.3); and (3) the effect of passive manual therapy mobilizations on kinematic variables of the neck during fast axial head rotation. RESULTS: (1) Intra-class correlation coefficients ranged from moderate (0.57 (0.06-0.80)) to excellent (0.96 (0.91-0.98)). (2) Kinematic performance during fast axial rotations of the head was significantly altered in ANSP compared to HCP (age-adjusted) for one variable: the time between peaks of acceleration and deceleration (p<0.019). No significant difference was observed between ANSP with upper vs lower spinal pain localization. (3) After the intervention, there was a significant effect on several kinematic variables, e.g., ANSP improved peak speed (p<0.007) and performance of the DidRen laser test (p<0.001), with effect sizes ranging from small to medium. CONCLUSION: (1) The DidRen laser test is reliable. (2) A significant reduction in time between acceleration and deceleration peaks was observed in ANSP compared to HCP, but with no significant effect of spinal pain location on kinematic variables was found. (3) We found that neck pain decreased after passive manual therapy mobilizations with improvements of several kinematic variables. TRIAL REGISTRATION: Registration Number: NCT04407637.

Low-Cost Sensors and Biological Signals.

Low-cost sensors, i [...].

DYSKIMOT: An Ultra-Low-Cost Inertial Sensor to Assess Head's Rotational Kinematics in Adults during the Didren-Laser Test.

Various noninvasive measurement devices can be used to assess cervical motion. The size, complexity, and cost of gold-standard systems make them not suited to clinical practice, and actually difficult to use outside a dedicated laboratory. Nowadays, ultra-low-cost inertial measurement units are available, but without any packaging or a user-friendly interface. The so-called DYSKIMOT is a home-designed, small-sized, motion sensor based on the latter technology, aiming at being used by clinicians in "real-life situations". DYSKIMOT was compared with a gold-standard optoelectronic system (Elite). Our goal was to evaluate the DYSKIMOT accuracy in assessing fast head rotations kinematics. Kinematics was simultaneously recorded by systems during the execution of the DidRen Laser test and performed by 15 participants and nine patients. Kinematic variables were computed from the position, speed and acceleration time series. Two-way ANOVA, Passing-Bablok regressions, and dynamic time warping analysis showed good to excellent agreement between Elite and DYSKIMOT, both at the qualitative level of the time series shape and at the quantitative level of peculiar kinematical events' measured values. In conclusion, DYSKIMOT sensor is as relevant as a gold-standard system to assess kinematical features during fast head rotations in participants and patients, demonstrating its usefulness in both clinical practice and research environments.

Timed Up and Go and Six-Minute Walking Tests with Wearable Inertial Sensor: One Step Further for the Prediction of the Risk of Fall in Elderly Nursing Home People.

Assessing the risk of fall in elderly people is a difficult challenge for clinicians. Since falls represent one of the first causes of death in such people, numerous clinical tests have been created and validated over the past 30 years to ascertain the risk of falls. More recently, the developments of low-cost motion capture sensors have facilitated observations of gait differences between fallers and nonfallers. The aim of this study is twofold. First, to design a method combining clinical tests and motion capture sensors in order to optimize the prediction of the risk of fall. Second to assess the ability of artificial intelligence to predict risk of fall from sensor raw data only. Seventy-three nursing home residents over the age of 65 underwent the Timed Up and Go (TUG) and six-minute walking tests equipped with a home-designed wearable Inertial Measurement Unit during two sets of measurements at a six-month interval. Observed falls during that interval enabled us to divide residents into two categories: fallers and nonfallers. We show that the TUG test results coupled to gait variability indicators, measured during a six-minute walking test, improve (from 68% to 76%) the accuracy of risk of fall's prediction at six months. In addition, we show that an artificial intelligence algorithm trained on the sensor raw data of 57 participants reveals an accuracy of 75% on the remaining 16 participants.

Three-Dimensional Spinal Position With and Without Manual Distraction Load Increases Spinal Height.

OBJECTIVE: The purpose of this study was to investigate if spinal height increases using 3-dimensional (3-D) spinal position with and without manual distraction load and to assess the correlation between spine height changes and degrees of trunk rotation. METHODS: Fifty-six participants were randomly placed in one of two groups: (1) 3-D spinal position with manual distraction load, and (2) without manual distraction load. Spinal height was measured before and after the interventions using a stadiometer. For the statistical analysis, we used a 2 (Loading status: pre- versus post-intervention height) X 2 (3-D spinal position: with versus without manual distraction load) repeated measures Analysis of Variance (ANOVA) was used to identify significant interaction and main effects. Paired t-tests were used to calculate differences in spinal height changes between the two interventions. Pearson correlation coefficient was used to measure correlations between changes in spinal heights and degrees of trunk rotation. RESULTS: Mean spinal height increase with 3-D spinal position with and without manual distraction load was 6.30 mm (±6.22) and 5.69 mm (±4.13), respectively. No significant interaction effect was present between loading status and 3-D spinal position but a significant main effect in loading status was. Paired t-tests revealed significant differences in spinal heights between pre-and post-3-D spinal position with and without manual distraction load. No significant correlation was measured between trunk rotation and spinal height changes. CONCLUSION: 3-D spinal position with or without distraction load increased spinal height. This suggests that 3-D spinal positioning without manual distraction could be used in home settings to help maintain intervertebral disc (IVD) health.

Clinical and MRI changes of puborectalis and iliococcygeus after a short period of intensive pelvic floor muscles training with or without instrumentation : A prospective randomized controlled trial.

PURPOSE: This study evaluates the impact of a 3-week period of intensive pelvic floor muscles training (PFMT), with or without instrumentation, on clinical and static magnetic resonance imaging (MRI) changes of puborectalis (PR) and iliococcygeus (IL) muscles. METHODS: 24 healthy young women were enrolled in the study and 17 achieved the 9 sessions of 30 min training exercises and conducted all assessments. Participants were randomly assigned in two training groups: voluntary contractions combined with hypopressive exercises (HYPO) or biofeedback exercises combined with transvaginal electrical stimulations (ELEC). Clinical and T2-weighted MRI assessments were realized before and after training. RESULTS: Modified Oxford Grading System (MOGS) scores for left PR and perineal body significantly increased in the two groups (p = 0.039, p = 0.008), but MOGS score for right PR significantly increased only in HYPO (p = 0.020). Muscle volumes of right and left IL significantly decreased (p = 0.040, p = 0.045) after training as well as signal intensities of right and left PR (p = 0.040, p = 0.021) and thickness of right and left IL at mid-vagina location (p = 0.012, p = 0.011). CONCLUSIONS: A short period of intensive PFMT induces clinical and morphological changes in PFMs at rest suggesting a decrease in IL volume and adipose content of PR. Although the results suggested that an intensive non-instrumented PFMT is as effective as an instrumented training, future controlled studies with greater sample sizes are needed to establish the relative and absolute effectiveness of each of the two interventions.

Unstable footwear as a speed-dependent noise-based training gear to exercise inverted pendulum motion during walking.

Previous research on unstable footwear has suggested that it may induce mechanical noise during walking. The purpose of this study was to explore whether unstable footwear could be considered as a noise-based training gear to exercise body center of mass (CoM) motion during walking. Ground reaction forces were collected among 24 healthy young women walking at speeds between 3 and 6 km h-1 with control running shoes and unstable rocker-bottom shoes. The external mechanical work, the recovery of mechanical energy of the CoM during and within the step cycles, and the phase shift between potential and kinetic energy curves of the CoM were computed. Our findings support the idea that unstable rocker-bottom footwear could serve as a speed-dependent noise-based training gear to exercise CoM motion during walking. At slow speed, it acts as a stochastic resonance or facilitator that reduces external mechanical work; whereas at brisk speed it acts as a constraint that increases external mechanical work and could mimic a downhill slope.

Resonance tuning of rhythmic movements is disrupted at short time scales: A centrifuge study.

The human body exploits its neural mechanisms to optimize actions. Rhythmic movements are optimal when their frequency is close to the natural frequency of the system. In a pendulum, gravity modulates this spontaneous frequency. Participants unconsciously adjust their natural pace when cyclically moving the arm in altered gravity. However, the timescale of this adaptation is unexplored. Participants performed cyclic movements before, during, and after fast transitions between hypergravity levels (1g-3g and 3g-1g) induced by a human centrifuge. Movement periods were modulated with the average value of gravity during transitions. However, while participants increased movement pace on a cycle basis when gravity increased (1g-3g), they did not decrease pace when gravity decreased (3g-1g). We highlight asymmetric effects in the spontaneous adjustment of movement dynamics on short timescales, suggesting the involvement of cognitive factors, beyond standard dynamical models.

Occupational Risk Factors for Musculoskeletal Disorders among Workers in Dairy Diversification.

BACKGROUND: In a changing European agricultural context, diversification of dairy farms is gaining attention. This study seeks to (1) assess musculoskeletal pain prevalence associated with tasks such as butter, yogurt, and cheese production; and (2) analyze associated risks. METHODS: Observing 31, mostly female, workers, we utilized the ERGOROM questionnaire, a methodology adapted from the Institut National de Recherche et de Sécurité, and Key Indicator Method forms. RESULTS: Findings revealed that tasks like load carrying (42% of workers), manual work (17%), and awkward postures (14%) resulted in musculoskeletal pain, predominantly in the lower back (65%), neck (39%), and dominant upper limb areas (shoulder: 61%, elbow: 26%, and wrist: 65%). While psychosocial risks remained low, concerns arose from workload, hygiene standards, and resource unpredictability. CONCLUSIONS: As dairy farming evolves from artisanal to semi-industrial, our study emphasizes the importance of ergonomic adaptations to protect farmers' health and prevent musculoskeletal disorders during diversification.

Evaluating cervical spine mobility and Fitt's law compliance: The DidRen laser test adapted for virtual reality with age and sex effects.

Cervical spine mobility assessment is crucial in rehabilitation to monitor patient progress. This study introduces the DidRen VR test, a virtual reality (VR) adaptation of the conventional DidRen laser test, aimed at evaluating cervical spine mobility. We conducted a cross-sectional study involving fifty healthy participants that underwent the DidRen VR test. The satisfaction of Fitts' law within this VR adaptation was examined and we analyzed the effects of age and sex on the sensorimotor performance metrics. Our findings confirm that Fitts' law is satisfied, demonstrating a predictable relationship between movement time and the index of difficulty, which suggest that the DidRen VR test can simulate real-world conditions. A clear influence of age and sex on performance was observed, highlighting significant differences in movement efficiency and accuracy across demographics, which may necessitate personalized assessment strategies in clinical rehabilitation practices. The DidRen VR test presents an effective tool for assessing cervical spine mobility, validated by Fitts' law. It offers a viable alternative to real-world method, providing precise control over test conditions and enhanced engagement for participants. Since age and sex significantly affect sensorimotor performance, personalized assessments are essential. Further research is recommended to explore the applicability of the DidRen VR test in clinical settings and among patients with neck pain.

Description and rules of a new card game to learn clinical reasoning in musculoskeletal physiotherapy.

Teaching hypothetico-deductive clinical reasoning (CR) should be an essential part of the physiotherapy education system, but currently there are very few learning tools for teachers in the musculoskeletal discipline. The aim of this article was to describe and present the rules of a new game-based and structured didactic tool that can be used by teachers for 'players' (students and licensed clinicians) to learn systematic CR in musculoskeletal physiotherapy.Our tool is based on the 'Happy Families' card game, and we propose to use it as part of a classic musculoskeletal subjective examination-based hypothesis category framework and the International Classification of Functioning, Disability and Health model. It allows players to dynamically formulate hypotheses from clinical case studies. Each 'Family' of cards represents a hypothesis category. The game highlights the missing information and trains players to consider it in their CR.This game should efficiently structure all components of CR and is an interesting resource for all teachers. Its greatest strength is that it can be used with other category frameworks. Further studies are needed to assess the efficacy and efficiency of such a tool and to measure students' actual progress in learning the CR.

CHECGAIT: A Functional Electrical Stimulation Clinical Pathway to Reduce Foot Drop during Walking in Adult Patients with Upper Motor Neuron Lesions.

Foot drop during the swing phase of gait and at initial foot contact is a current kinematic abnormality that can occur following an upper motor neuron (UMN) lesion. Functional electrical stimulation (FES) of the common peroneal nerve through an assistive device is often used in neuro-rehabilitation to help patients regain mobility. Although there are FES-specific guideline recommendations, it remains a challenge for clinicians to appropriately select patients eligible for the daily use of FES devices, as very few health insurance systems cover its cost in Europe. In Luxembourg, since 2018, successfully completing an FES clinical pathway called CHECGAIT is a prerequisite to receiving financial coverage for FES devices from the national health fund (Caisse Nationale de Santé-CNS). This study describes the structure and steps of CHECGAIT and reports our experience with a cohort of 100 patients enrolled over a three-year period. The clinical and gait outcomes of all patients were retrospectively quantified, and a specific analysis was performed to highlight differences between patients with and without an FES device prescription at the end of a CHECGAIT. Several significant gait differences were found between these groups. These results and CHECGAIT may help clinicians to better select patients who can most benefit from this technology in their daily lives. In addition, CHECGAIT could provide significant savings to public health systems by avoiding unnecessary deliveries of FES devices.

Rethinking neck-related arm pain: hypothetical clinical scenarios to differentiate the underlying IASP-defined pain mechanisms.

Neck-related arm pain is frequently encountered in clinical settings, yet its underlying pain mechanisms remain elusive. While such pain radiating from the neck to the arm is often attributed to injuries or diseases of the nervous system (neuropathic pain), it can also arise from nociceptive (referred) or nociplastic sources. Regrettably, patients exhibiting this specific pain distribution are frequently diagnosed with varying terms, including 'cervicobrachialgia', 'cervicobrachial neuralgia', 'cervicobrachial pain syndrome', and 'cervical radiculopathy'. The ambiguity surrounding these diagnostic labels complicates the clinical reasoning process. It is imperative for clinicians to discern and comprehend the dominant pain mechanism. Three distinct hypothetical clinical scenarios depict patients with almost identical pain distribution but divergent dominant pain mechanisms. Within these scenarios, both subjective and objective examinations are employed to elucidate the dominant pain mechanism associated with neck-related arm pain: nociceptive, neuropathic, and nociplastic. Furthermore, clinicians must remain aware that the dominant pain mechanism can evolve over time.

Classification of Stiff-Knee Gait Kinematic Severity after Stroke Using Retrospective k-Means Clustering Algorithm.

Nowadays, a classification system for unilateral stiff-knee gait (SKG) kinematic severity in hemiparetic adult patients after stroke does not exist. However, such classification would be useful to the clinicians. We proposed the use of the k-means method in order to define unilateral SKG severity clusters in hemiparetic adults after stroke. A retrospective k-means cluster analysis was applied to five selected knee kinematic parameters collected during gait in 96 hemiparetic adults and 19 healthy adults from our clinical gait analysis database. A total of five discrete knee kinematic clusters were determined. Three clusters of SKG were identified, based on which a three-level severity classification was defined: unbend-knee gait, braked-knee gait, and frozen-limb gait. Preliminary construct validity of the classification was obtained. All selected knee kinematic parameters defining the five clusters and the majority of usual kinematic parameters of the lower limbs showed statistically significant differences between the different clusters. We recommend diagnosing SKG for values strictly below 40° of knee flexion during the swing phase. Clinicians and researchers are now able to specify the level of kinematic severity of SKG in order to optimize treatment choices and future clinical trial eligibility criteria.