BACKGROUND: Markerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia.
OBJECTIVE: The primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease.
METHODS: A systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review. .
RESULTS: Primarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models.
CONCLUSIONS: Despite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.

UNASSIGNED: Stone, MH, Hornsby, G, Mizuguchi, S, Sato, K, Gahreman, D, Duca, M, Carroll, K, Ramsey, MW, Stone, ME, and Haff, GG. The use of free weight squats in sports: a narrative review-squatting movements, adaptation, and sports performance: physiological. J Strength Cond Res 38(8): 1494-1508, 2024-The squat and its variants can provide numerous benefits including positively affecting sports performance and injury prevention, injury severity reduction, and rehabilitation. The positive benefits of squat are likely the result of training-induced neural alterations and mechanical and morphological adaptations in tendons, skeletal muscles, and bones, resulting in increased tissue stiffness and cross-sectional area (CSA). Although direct evidence is lacking, structural adaptations can also be expected to occur in ligaments. These adaptations are thought to beneficially increase force transmission and mechanical resistance (e.g., resistance to mechanical strain) and reduce the likelihood and severity of injuries. Adaptations such as these, also likely play an important role in rehabilitation, particularly for injuries that require restricted use or immobilization of body parts and thus lead to a consequential reduction in the CSA and alterations in the mechanical properties of tendons, skeletal muscles, and ligaments. Both volume and particularly intensity (e.g., levels of loading used) of training seem to be important for the mechanical and morphological adaptations for at least skeletal muscles, tendons, and bones. Therefore, the training intensity and volume used for the squat and its variations should progressively become greater while adhering to the concept of periodization and recognized training principles.

Biomechanical analysis of the human spine is crucial to understanding injury patterns. Motion capture technology has gained attention due to its non-invasive nature. Nevertheless, traditional motion capture studies consider the spine a single rigid segment, although its alignment changes during movement. Moreover, guidelines that indicate where markers should be placed for a specific exercise do not exist. This study aims to review the methods used to assess spine biomechanics using motion capture systems to determine the marker sets used, the protocols used, the resulting parameters, the analysed activities, and the characteristics of the studied populations. PRISMA guidelines were used to perform a Scoping Review using SCOPUS and Web of Science databases. Fifty-six journal and conference articles from 1997 to 2023 were considered for the analysis. This review showed that Plug-in-Gait is the most used marker set. The lumbar spine is the segment that generates the most interest because of its high mobility and function as a weight supporter. Furthermore, angular position and velocity are the most common outcomes when studying the spine. Walking, standing, and range of movement were the most studied activities compared to sports and work-related activities. Male and female participants were recruited similarly across all included articles. This review presents the motion capture techniques and measurement outcomes of biomechanical studies of the human spine, to help standardize the field. This work also discusses trends in marker sets, study outcomes, studied segments and segmentation approaches.

UNASSIGNED: This scoping review aims to describe how Bobath concept is conceptualized, operationalized, and studied in adult neurorehabilitation.
UNASSIGNED: The Joanna Briggs Institute (JBI) and the Preferred Reporting Items for Scoping Reviews (PRISMA-ScR) guidelines were adopted. Non-scientific and research articles were searched in electronic databases PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, Web of Science, ScienceDirect, and Physiotherapy Evidence Database (PEDro), with the keywords \"Bobath\" or \"Neurodevelopmental Treatment\", published in English, Spanish, and Portuguese, between 2013 and 2023.
UNASSIGNED: Of the 78 publications identified, 31 articles addressed the conceptual underpinnings of Bobath concept (seven theoretical papers, seven Delphi/surveys/mixed methods studies, four qualitative studies, one scoping review, 10 letters to the editor, and two editorials), comprising five themes: (a) theoretical principles; (b) clinical principles; (c) clinical reasoning; (d) conceptualizing movement; and, current (e) evidence debate. The revised definition and the Model of Bobath Clinical Practice provide a clarification of the unique aspects of Bobath concept. A new clinical skill was identified beyond facilitation - visuospatial kinesthetic perception - as well as how Bobath experts conceptualize movement, which are all integral to clinical reasoning.
UNASSIGNED: This review provides an updated Bobath clinical framework that gathers the theoretical foundations and clinical practice principles that require careful consideration in the design of future intervention studies.Implications for rehabilitationThis scoping review consolidates the clinical and theoretical principles of contemporary Bobath practice, providing a clear framework for clinicians.The Model of Bobath Clinical Practice (MBCP) framework enables detailed documentation of movement analysis and movement diagnosis, guiding clinical reasoning and interventions.This review identifies fundamental principles and practices to inform future Bobath intervention studies, ensuring their clinical relevance.A framework with specific recommendations has been developed to guide Bobath intervention studies, enhancing the integration of clinical practice, education, and research.

Brain-computer interfaces (BCIs) provide a communication interface between the brain and external devices and have the potential to restore communication and control in patients with neurological injury or disease. For the invasive BCIs, most studies recruited participants from hospitals requiring invasive device implantation. Three widely used clinical invasive devices that have the potential for BCIs applications include surface electrodes used in electrocorticography (ECoG) and depth electrodes used in Stereo-electroencephalography (SEEG) and deep brain stimulation (DBS). This review focused on BCIs research using surface (ECoG) and depth electrodes (including SEEG, and DBS electrodes) for movement decoding on human subjects. Unlike previous reviews, the findings presented here are from the perspective of the decoding target or task. In detail, five tasks will be considered, consisting of the kinematic decoding, kinetic decoding,identification of body parts, dexterous hand decoding, and motion intention decoding. The typical studies are surveyed and analyzed. The reviewed literature demonstrated a distributed motor-related network that spanned multiple brain regions. Comparison between surface and depth studies demonstrated that richer information can be obtained using surface electrodes. With regard to the decoding algorithms, deep learning exhibited superior performance using raw signals than traditional machine learning algorithms. Despite the promising achievement made by the open-loop BCIs, closed-loop BCIs with sensory feedback are still in their early stage, and the chronic implantation of both ECoG surface and depth electrodes has not been thoroughly evaluated.

UNASSIGNED: Wearable trunk exoskeletons hold immense potential in fields such as healthcare and industry. Previous research has indicated that intention recognition control plays a crucial role in users\' daily use of exoskeletons.
UNASSIGNED: This review aims to discuss the characteristics of intention recognition control schemes for intelligent trunk exoskeletons under different control objectives over the past decade.
UNASSIGNED: Considering the relatively late development of active trunk exoskeletons, we selected papers published in the last decade (2013 to 2023) from the Web of Science, PubMed, and IEEE Xplore databases. In total, 50 articles were selected and examined based on four control objectives.
UNASSIGNED: In general, we found that researchers focus on trunk exoskeleton devices designed for assistance and motor augmentation, which rely more on body movement signals as a source for intention recognition.
UNASSIGNED: Based on these results, we identify and discuss several promising research directions that may help to attain a widely accepted control methods, thereby advancing further development of trunk exoskeleton technology.

The aim of this systematic review was to assess the effects of plyometric-jump training (PJT) on the physical fitness of youth with cerebral palsy (CP) compared with controls (i.e., standard therapy). The PRISMA 2020 guidelines were followed. Eligibility was assessed using the PICOS approach. Literature searches were conducted using the PubMed, Web of Science, and SCOPUS databases. Methodological study quality was assessed using the PEDro scale. Data were meta-analyzed by applying a random-effects model to calculate Hedges\' g effect sizes (ES), along with 95% confidence intervals (95% CI). The impact of heterogeneity was assessed (I2 statistic), and the certainty of evidence was determined using the GRADE approach. Eight randomized-controlled studies with low-to-moderate methodological quality were included, involving male (n = 225) and female (n = 138) youth aged 9.5 to 14.6 years. PJT interventions lasted between 8 and 12 weeks with 2-4 weekly sessions. Compared with controls, PJT improved the muscle strength (ES = 0.66 [moderate], 95% CI = 0.36-0.96, p < 0.001, I2 = 5.4%), static (ES = 0.69 [moderate], 95% CI= 0.33-1.04, p < 0.001, I2 = 0.0%) and dynamic balance (ES = 0.85 [moderate], 95% CI = 0.12-1.58, p = 0.023, I2 = 81.6%) of youth with CP. Therefore, PJT improves muscle strength and static and dynamic balance in youth with CP compared with controls. However, more high-quality randomized-controlled trials with larger sample sizes are needed to provide a more definitive recommendation regarding the use and safety of PJT to improve measures of physical fitness.

BACKGROUND: A majority of employees in the industrial world spend most of their working time in a seated position. Monitoring sitting postures can provide insights into the underlying causes of occupational discomforts such as low back pain.
OBJECTIVE: This study focuses on the technologies and algorithms used to classify sitting postures on a chair with respect to spine and limb movements, using sensors and wearables such as inertial measurement units, pressure or piezoresistive sensors, accelerometers or gyroscopes, combined with machine learning approaches.
METHODS: A total of three electronic literature databases were surveyed to identify studies classifying sitting postures in adults. Quality appraisal was performed to extract critical details and assess biases in the shortlisted papers.
RESULTS: A total of 14 papers were shortlisted from 952 papers obtained after a systematic search. The majority of the studies used pressure sensors to measure sitting postures, whereas neural networks were the most frequently used approaches for classification tasks in this context. Only 2 studies were performed in a free-living environment. Most studies presented ethical and methodological shortcomings. Moreover, the findings indicate that the strategic placement of sensors can lead to better performance and lower costs.
CONCLUSIONS: The included studies differed in various aspects of design and analysis. The majority of studies were rated as medium quality according to our assessment. Our study suggests that future work for posture classification can benefit from using inertial measurement unit sensors, since they make it possible to differentiate among spine movements and similar postures, considering transitional movements between postures, and using three-dimensional cameras to annotate the data for ground truth. Finally, comparing such studies is challenging, as there are no standard definitions of sitting postures that could be used for classification. In addition, this study identifies five basic sitting postures along with different combinations of limb and spine movements to help guide future research efforts.

Work-related diseases and disorders remain a significant global health concern, necessitating multifaceted measures for mitigation. One potential measure is work technique training utilizing augmented feedback through wearable motion capture systems. However, there exists a research gap regarding its current effectiveness in both real work environments and controlled settings, as well as its ability to reduce postural exposure and retention effects over short, medium, and long durations. A rapid review was conducted, utilizing two databases and three previous literature reviews to identify relevant studies published within the last twenty years, including recent literature up to the end of 2023. Sixteen studies met the inclusion criteria, of which 14 were of high or moderate quality. These studies were summarized descriptively, and the strength of evidence was assessed. Among the included studies, six were rated as high quality, while eight were considered moderate quality. Notably, the reporting of participation rates, blinding of assessors, and a-priori power calculations were infrequently performed. Four studies were conducted in real work environments, while ten were conducted in controlled settings. Vibration feedback was the most common feedback type utilized (n = 9), followed by auditory (n = 7) and visual feedback (n = 1). All studies employed corrective feedback initiated by the system. In controlled environments, evidence regarding the effectiveness of augmented feedback from wearable motion capture systems to reduce postural exposure ranged from strong evidence to no evidence, depending on the time elapsed after feedback administration. Conversely, for studies conducted in real work environments, the evidence ranged from very limited evidence to no evidence. Future reach needs are identified and discussed.

Biomechanical analysis of human movement plays an essential role in understanding functional changes in people with Amyotrophic Lateral Sclerosis (ALS), providing information on muscle impairment. Studies suggest that surface electromyography (sEMG) may be able to quantify muscle activity, identify levels of fatigue, assess muscle strength, and monitor variation in limb movement. In this article, a systematic review protocol will analyze the psychometric properties of the sEMG regarding the clinical data on the skeletal muscles of people with ALS. This protocol uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological tool. A specific field structure was defined to reach each phase. Nine scientific databases (PubMed, Web of Science, Embase, Elsevier, IEEE, Google Scholar, SciELO, PEDro, LILACS E CENTRAL) were searched. The framework developed will extract data (i.e. study information, sample information, sEMG information, intervention, and outcomes) from the selected studies using a rigorous approach. The data will be described quantitatively using frequency and trend analysis methods, and heterogeneity between the included studies will be assessed using the I2 test. The risk of bias will be summarized using the most recent prediction model risk of bias assessment tool. Be sure to include relevant statistics here, such as sample sizes, response rates, P values or Confidence Intervals. Be specific (by stating the value) rather than general (eg, \"there were differences between the groups\"). This protocol will map out the construction of a systematic review that will identify and synthesize the advances in movement analysis of people with ALS through sEMG, using data extracted from articles.