Rehabilitation Applications Research Articles

Exploring knowledge, awareness and perception of Clinical Physical Therapist toward Artificial intelligence application in Physical Therapy and Rehabilitation

Exploring knowledge, awareness and perception of Clinical Physical Therapist toward Artificial intelligence application in Physical Therapy and Rehabilitation

Design of a supersoft, ultra-stretchable, and 3D printable hydrogel electrical bioadhesive interface for electromyography monitoring

Electromyography (EMG) monitoring has been extensively employed for critical applications in medicine, sports science, and rehabilitation. However, the mechanical mismatch between conventional EMG electrodes and the skin can lead to electrode detachment upon significant skin deformation. To address this limitation, we develop a PEDOT:PSS-based hydrogel electrical bioadhesive interface (EBI) that incorporates molecular doping and robust adhesion strategies to achieve excellent mechanical compatibility with biological tissues. This hydrogel EBI is fabricated using direct writing of printable inks followed by in-situ thermal initiation, enabling the creation of customizable patterns with high shape fidelity. The resultant 3D-printed PEDOT:PSS-based hydrogel EBI exhibits supersoft properties (Young's modulus 5-8.5 kPa), ultra-stretchability (1,175% strain), robust adhesion (>133 kPa), and outstanding electrochemical performance (CIC reduction by 0.45% over 100,000 cycles). Additionally, we further develop a PEDOT:PSS-based hydrogel electrode specifically for stable EMG signal recording. This electrode outperforms superior signal-to-noise ratio (SNR) performance compared to commercial electrodes in EMG monitoring.

Real-Time IMU-Based Kinematics in the Presence of Wireless Data Drop.

Wireless inertial motion capture holds promise for real-time human-machine interfaces and home-based rehabilitation applications. However, wireless data drop can cause significant estimation errors deteriorating performance or even making the system unusable. It is currently unclear how to estimate non-periodic kinematics with wearable inertial measurement units (IMUs) in the presence of wireless data drop (packet loss). We thus propose a novel inference encoder-decoder network model for real-time kinematics during dynamic movement. Twenty-four healthy subjects performed yoga, golf, swimming, dance, and badminton movement activities while wearing IMUs and 10-90% of each IMU's data were randomly removed to determine the effects of data drop on estimation accuracy with and without the proposed model. Results demonstrated a reduction in RMSE of 45.2% to 51.5% in the upper limb kinematic estimation of the proposed model compared to the No Prediction strategy, and a reduction of 19.1% to 31.3% of the proposed model compared with an baseline LSTM model. In addition, the proposed model has significantly less error (p<0.05) than the No Prediction strategy and the baseline LSTM model for 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% data drop. These results could enable wearable, wireless IMU dynamic motion analysis and assessment with reduced kinematic estimation error in the presence of varying amounts of wireless data drop and thus could further facilitate human-machine interaction and home-based medical assessment and treatment.

The Role Of Investigators In The Application Of Restorative Justice And Rehabilitation To Victims Of Drug Abuse In The Belawan Port Police

This study aims to determine the application of restorative justice and rehabilitation in the case of narcotics crime in legislation, the role of investigators in implementing restorative justice and rehabilitation in the Belawan jurisdiction, as well as the obstacles faced by investigators in implementing restorative justice and rehabilitation in the region. The research method used in this study is empirical juridical research that combines elements of law and scientific method. This study uses a qualitative approach with data collection techniques through interviews and document studies. The data sources consist of primary data obtained through observation, interviews, and questionnaires, as well as secondary data derived from primary and secondary legal materials. Data analysis is done descriptively by grouping, interpreting, and summarizing the data obtained. Investigators have an important role in handling cases of victims of drug abuse, including in the investigation, investigation, and rehabilitation. The implementation of restorative justice and rehabilitation at the Belawan Port Police Station has been carried out, but there are still obstacles such as lack of knowledge and skills of investigators, lack of support and facilities, and lack of community involvement. Increased training for investigators and stronger cooperation with communities and rehabilitation institutions are needed to improve the effectiveness of Drug Abuse Prevention.

Advances in Markerless Motion Capture Systems: A Review of OpenCap and Its Applications

Motion capture technology has long been a cornerstone of biomechanical research and analysis, traditionally relying on marker-based systems. However, these systems have inherent limitations, including high costs, time-consuming setup, and constraints on natural movement. Recent advancements in computer vision and machine learning have paved the way for markerless motion capture systems, such as OpenCap, which offer a more accessible and natural approach to biomechanical analysis. This review focuses on OpenCap, exploring its accuracy, challenges, and future potential, while comparing it with traditional motion capture technologies and discussing its applications in sports, clinical rehabilitation, and everyday use. Areas in need of refinement, such as improving pose estimation algorithms and addressing inter-trial variability, are identified as key future research directions. Other markerless systems are also compared in terms of advantages, limitations, and application. The findings suggest that while OpenCap and similar systems hold significant promise, further research and refinement are necessary to fully realize their potential and integrate them seamlessly into various biomechanical applications.

Effectiveness of a check-up for rehabilitation and prevention needs in primary care

Abstract Background General practitioners play a central role in initiating rehabilitation and prevention services. However, systematic screening for rehabilitation and prevention needs has not been carried out in general practices so far. The legislation encourages the implementation and evaluation of so-called ‘check-up 45+’, which target individuals aged 45 and older. The study aims to evaluate the effectiveness of a check-up 45+ in primary care. Methods A pragmatic, randomized controlled trial was conducted in 26 general practices in the German states of Berlin and Brandenburg among patients aged 45 to 59 years (DRKS00028303). The control group (n = 695) received usual care plus a questionnaire on sociodemographic and health-related characteristics. The intervention group (n = 706) completed additionally the 2-page ‘screening 45+’, which captures rehabilitation and prevention needs in five dimensions. After algorithm-based ad hoc evaluation by practice staff, the general practice could modify the recommendation based on available information (e.g., diagnoses, social situation). Information and application documents were provided in case of identified needs. Applications (primary outcome) and approvals (secondary outcome) of rehabilitation and prevention services were recorded using routine data. Results In the intervention group, 64.2% were women, compared to 63.0% in the control group (mean age 52.1 (SD 4.3) and 52.5 (SD 4.4) years). In the intervention group, 85 applications (12.0%) for medical rehabilitation or prevention services were submitted within two months after the study participation, compared to 20 applications (2.9%) in the control group (p &amp;lt; 0.001). The number of approvals for these services was 59 vs. 17 (p &amp;lt; 0.001). Conclusions The application rate for rehabilitation and prevention services was significantly higher in the intervention group compared to the control group, with a relative risk difference by a factor of 4 and an absolute risk difference of 9.1%pt. Key messages • The implementation of a check-up 45+ in primary care leads to a higher rate of applications for rehabilitation and prevention services compared to usual care. • The check-up 45+ may assist general practitioners in systematically identifying rehabilitation and prevention needs of their patients and in applying for these services.

Establishing the Reliability of the GaitON® Motion Analysis System: A Foundational Study for Gait and Posture Analysis in a Healthy Population

Background: Gait and posture analysis plays a crucial role in understanding human movement, with significant applications in rehabilitation, sports science, and clinical settings. The GaitON® system, a 2D motion analysis tool, provides an accessible and cost-effective method for assessing gait and posture. However, its reliability in clinical practice, particularly for intra-rater consistency, remains to be evaluated. This study aims to assess the intra-rater reliability of the GaitON® system in a healthy population, focusing on gait and posture parameters. Methods: A total of 20 healthy participants (10 males and 10 females) aged 18 to 50 years were recruited for the study. Each participant underwent gait and posture assessments using the GaitON® system on two separate occasions, spaced one week apart. Video recordings from anterior and posterior views were used to analyze gait, while images from anterior, posterior, and lateral views were captured to assess posture with markers placed on key anatomical landmarks. The reliability of the measurements was analyzed using intraclass correlation coefficients (ICC), a standard error of measurement (SEM), and the smallest detectable difference (SDD) method. Results: The GaitON® system demonstrated excellent intra-rater reliability across a wide range of gait and posture parameters. ICC values for gait parameters, including hip, knee, and ankle joint angles, ranged from 0.90 to 0.979, indicating strong consistency in repeated measurements. Similarly, ICC values for posture parameters, such as the head alignment, shoulder position, and ASIS alignment, were above 0.90, reflecting excellent reliability. SEM values were low across all parameters, with the smallest SEM recorded for the hip joint angle (0.37°), and SDD values further confirmed the precision of the system. Conclusion: The GaitON® system provides reliable and consistent measurements for both gait and posture analysis in healthy individuals. Its high intra-rater reliability and low measurement error make it a promising tool for clinical and sports applications. Further research is needed to validate its use in clinical populations and compare its performance to more complex 3D motion analysis systems.

Improving Collaborative Interactions Between Humans and Artificial Intelligence to Achieve Optimal Patient Outcomes in the Healthcare Industry

The introduction of Artificial Intelligence (AI) into the healthcare industry holds immense promise for improving patient outcomes. However, the interaction between healthcare professionals and AI systems is critical to fully realize the potential benefits. Artificial intelligence (AI) applications have transformed healthcare. This study is based on a general literature review uncovering the role of Al in healthcare and focuses on the following key aspects: medical imaging and diagnostics, virtual patient care, medical research and drug discovery, patient engagement and compliance, rehabilitation and other administrative applications. The impact of AI is observed in detecting clinical conditions in medical imaging and diagnostic services, controlling the outbreak of coronavirus disease 2019 (COVID-19) with early diagnosis, providing virtual patient care using Ai-powered tools, managing electronic health records, augmenting patient engagement and compliance with the treatment plan, reducing the administrative workload of healthcare professionals (HCPs), discovering new drugs and vaccines, spotting medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. Nevertheless, this science pitch meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs’ belief in enhancing acceptance and boosting significant health precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.

The Role of Bio-Inspired Soft Robotic Gloves in Stroke Rehabilitation: A Comprehensive Analytical Review

Stroke is a leading cause of long-term disability, with many survivors experiencing impaired motor function. Traditional rehabilitation methods often face limitations in achieving full functional recovery. In recent years, bio-inspired soft robotic gloves have emerged as a promising solution for enhancing stroke rehabilitation, mimicking the natural movement and adaptability of biological systems. This paper provides a comprehensive analytical review of bio-inspired soft robotic gloves designed for stroke rehabilitation, focusing on their development, fabrication methods and therapeutic applications. The primary objective of this review is to evaluate the role of bio-inspired designs in the creation of soft robotic gloves and assess their effectiveness in facilitating motor recovery post-stroke. A systematic analysis of existing literature is conducted, exploring various fabrication techniques, including soft material integration, actuators and sensors, as well as the application of these gloves in clinical and therapeutic settings. Findings from this review reveal that bio-inspired soft robotic gloves show significant potential in improving patient outcomes by enhancing finger and hand movement through assisted motor control. These devices offer advantages in terms of comfort, flexibility and adaptability, allowing for prolonged and intensive rehabilitation sessions. However, limitations remain, such as the high cost of fabrication, challenges in achieving precise motor control and the lack of large-scale clinical trials to validate long-term efficacy. The research has several implications: (1) Theoretical: advancing the understanding of bio-inspired design principles in soft robotics; (2) Methodological: highlighting fabrication techniques that enhance glove performance and user adaptability. This review offers original value by consolidating and analysing recent developments in bio-inspired soft robotic gloves, contributing to both the academic literature and practical applications in stroke rehabilitation. It emphasizes the necessity of future research to address current limitations, especially in optimizing performance and reducing production costs, while enhancing patient outcomes.

High-Definition Trans-Spinal Current Stimulation Improves Balance and Somatosensory Control: A Randomised, Placebo-Controlled Trial.

To investigate and compare the effects of three different high-definition (HD) non-invasive current stimulation (NICS) protocols on the spinal cord on support balance and somatosensory abilities in healthy young people. Fifty-eight students were enrolled in this crossover study. All participants underwent application of (i) 1.5 mA anodal high-definition trans spinal direct current stimulation (HD-tsDCS), (ii) 1.5 mA cathodal HD-tsDCS, (iii) 1.5 mA high-definition trans spinal alternating current stimulation (HD-tsACS), and (iv) sham HD-tsDCS/ACS over the eighth thoracic vertebra in a randomised order. Balance (Y Balance test), deep sensitivity (Tuning Fork Test), and superficial sensitivity (Monofilament Test) of the lower limbs were tested immediately before and after each intervention. Balance ability improved significantly following anodal HD-tsDCS and HD-tsACS compared with that following sham HD-tsDCS/ACS. Similarly, deep sensitivity increased significantly with anodal HD-tsDCS and HD-tsACS compared to that with sham HD-tsDCS/ACS and cathodal HD-tsDCS. Furthermore, superficial sensitivity improved significantly following anodal HD-tsDCS compared with that after HD-tsACS and cathodal HD-tsDCS. Our data show that HD-tsNICS effectively modulates the balance and somatosensory control of the lower limbs. Several diseases are associated with illness-induced changes in the spinal network in parallel with sensorimotor disabilities. Non-invasive spinal modulation may be a favourable alternative to conventional brain applications in rehabilitation. Future studies should therefore investigate these promising approaches among cohorts of patients with disabilities.

AI Applications in Adult Stroke Recovery and Rehabilitation: A Scoping Review Using AI

Stroke is a leading cause of long-term disability worldwide. With the advancements in sensor technologies and data availability, artificial intelligence (AI) holds the promise of improving the amount, quality and efficiency of care and enhancing the precision of stroke rehabilitation. We aimed to identify and characterize the existing research on AI applications in stroke recovery and rehabilitation of adults, including categories of application and progression of technologies over time. Data were collected from peer-reviewed articles across various electronic databases up to January 2024. Insights were extracted using AI-enhanced multi-method, data-driven techniques, including clustering of themes and topics. This scoping review summarizes outcomes from 704 studies. Four common themes (impairment, assisted intervention, prediction and imaging, and neuroscience) were identified, in which time-linked patterns emerged. The impairment theme revealed a focus on motor function, gait and mobility, while the assisted intervention theme included applications of robotic and brain–computer interface (BCI) techniques. AI applications progressed over time, starting from conceptualization and then expanding to a broader range of techniques in supervised learning, artificial neural networks (ANN), natural language processing (NLP) and more. Applications focused on upper limb rehabilitation were reviewed in more detail, with machine learning (ML), deep learning techniques and sensors such as inertial measurement units (IMU) used for upper limb and functional movement analysis. AI applications have potential to facilitate tailored therapeutic delivery, thereby contributing to the optimization of rehabilitation outcomes and promoting sustained recovery from rehabilitation to real-world settings.

Wearable and Implantable Soft Robots.

Soft robotics presents innovative solutions across different scales. The flexibility and mechanical characteristics of soft robots make them particularly appealing for wearable and implantable applications. The scale and level of invasiveness required for soft robots depend on the extent of human interaction. This review provides a comprehensive overview of wearable and implantable soft robots, including applications in rehabilitation, assistance, organ simulation, surgical tools, and therapy. We discuss challenges such as the complexity of fabrication processes, the integration of responsive materials, and the need for robust control strategies, while focusing on advances in materials, actuation and sensing mechanisms, and fabrication techniques. Finally, we discuss the future outlook, highlighting key challenges and proposing potential solutions.

AR-Based Upper Extremity Rehabilitation with Multimodal Feedback for Patients with Stroke and Parkinson’s Disease: A Scoping Review

Augmented Reality (AR) is increasingly used in various remote rehabilitation applications for patients with functional limitations. Providing multimodal feedback using auditory, visual, or haptic modalities can offer effective guidance to the patient while they perform self-supervised rehabilitation exercises. This review examines the current uses of AR with multimodal feedback in upper extremity rehabilitation applications built for stroke and Parkinson’s disease (PD) patients by synthesizing nine peer-reviewed studies. The review identified the improvement and engagement that AR-based rehabilitation provides to such patients. The current body of literature shows that AR-based rehabilitation with multimodal feedback is promising. However, technology and its application for rehabilitation use are still in their infancy. More research is required in selecting effective feedback modalities and clinically-relevant health outcome measures and in providing diverse rehabilitation tasks designed specifically for stroke survivors and PD population.

A Comprehensive Review of Electromyography in Rehabilitation: Detecting Interrupted Wrist and Hand Movements with a Robotic Arm Approach

Electromyography (EMG) is a diagnostic technique that measures the electrical activity generated by skeletal muscles. Utilizing electrodes placed either on the skin (surface EMG) or inserted directly into the muscle(intramuscular EMG), it detects electrical signals produced during muscle contractions. EMG is widely employed in clinical and research settings to assess muscle function, diagnose neuromuscular disorders,and guide rehabilitation therapy. Over the years, EMG has evolved from a basic measurement tool into an essential technology within clinical and research environments, propelled by advances in recording techniques and digital innovations. The integration of wearable technology and artificial intelligence (AI) has significantly expanded its applications, particularly in rehabilitation and sports science. By capturing muscle electrical activity through surface or intramuscular electrodes, EMG benefits from enhanced signal processing that improves accuracy and data analysis. Despite challenges such as signal interference and the complexities of movement patterns—especially in wrist and hand rehabilitation—EMG combined with robotic systems offers real-time feedback for precise and personalized therapy. However, obstacles like cost, complexity, and variability among patients still remain. Future advancements aim to make EMG more accessible and to integrate AI for tailored rehabilitation strategies, alongside improvements in sensors and wireless communication to enhance reliability and performance. This review explores various facets of EMG,from its fundamental principles to its application in detecting disrupted wrist and hand movements through robotic approaches. It provides a comprehensive analysis of EMG’s historical and technological evolution, recent innovations like AI and wearable devices, and its extensive applications in rehabilitation and sports science. Detailed case studies illustrate its effectiveness in areas such as stroke recovery and spinal cord injury rehabilitation. Additionally, the review addresses challenges like technical limitations and patient variability while emphasizing the integration of EMG with robotic systems for personalized therapy. It also discusses the significance of real-time feedback, future enhancements in AI and sensor technology, and the pressing need for more affordable, user-friendly solutions to improve therapeutic outcomes.

Application of pelvic floor rehabilitation in patients with colorectal cancer: a scoping review.

Pelvic floor rehabilitation is common in patients with colorectal cancer,the purpose of this study is to analyze the role of pelvic floor rehabilitation in patients with colorectal cancer and to understand the specific details of pelvic floor rehabilitation intervention in patients with colorectal cancer. Six databases were searched for this scoping review and reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews. A total of 1014 studies were searched, and 12 studies were finally included for analysis. The study found that pelvic floor rehabilitation for colorectal cancer patients can help improve bowel symptoms, quality of life, and psychological status of colorectal cancer patients after surgery, but details of the interventions for pelvic floor rehabilitation for colorectal cancer patients are not standardized. Pelvic floor rehabilitation has shown positive significance in patients with colorectal cancer, but there is a lack of uniform standards in the process of pelvic floor rehabilitation intervention in patients with colorectal cancer.

Pulmonary rehabilitation in patients with fibrotic interstitial lung disease

Cough, progressive exertional dyspnea, and exercise limitation are the main presenting symptoms in fibrotic interstitial lung disease (F-ILD). F-ILD is usually progressive, leading to heavy disease and socioeconomic burden. In addition to the drug therapy, pulmonary rehabilitation is an important part of comprehensive treatment in F-ILD patients. In recent years, the application of pulmonary rehabilitation in F-ILD patients has attracted the attention of clinicians and society. Meanwhile, pulmonary rehabilitation has widely applicated in F-ILD patients as it is beneficial to improve their symptoms, functional exercise and quality of life. This article provides a comprehensive review of pulmonary rehabilitation in F-ILD and proposes the principles and strategies, to prevent the progression or acute exacerbation of F-ILD and improve its application in F-ILD patients.

Reforming Indonesia’s Approach to Narcotics Offenses: A Call for Rehabilitation over Incarceration

This study examines the issue of prison overcrowding in Indonesia, with a particular focus on the impact of current penal policies related to drug-related offenses. The over-reliance on incarceration, especially for minor drug crimes, is identified as a significant contributor to the overcrowding crisis in correctional institutions. Despite legal provisions for rehabilitation as an alternative to imprisonment, inconsistent implementation has hindered efforts to address the root causes of drug-related crimes. The study advocates for a comprehensive reform of Indonesia’s penal system, emphasizing the need to shift from a punitive approach to one centered on rehabilitation and restorative justice. Such reforms are essential not only to alleviate overcrowding but also to ensure the humane treatment of individuals with substance use disorders, in line with international human rights standards. The study concludes with recommendations for enhancing the application of rehabilitation, increasing public awareness, and improving the monitoring of rehabilitation programs to foster a more equitable and effective criminal justice system.

Sensitization of Visually Induced Motion Sickness by Prior Provocative Physical Motion

INTRODUCTION: Habituation to motion has therapeutic applications for motion sickness desensitization and rehabilitation of patients with vestibular disease. Less attention has been devoted to the opposite process: sensitization. METHODS: Subjects (N = 50) were randomly allocated to four sequences: Baseline visual stimulus; then 15 min of time gap; cross-coupled motion (C-C) or a Control condition; then a time gap of 15 min or 2 h; then a retest visual stimulus. Motion exposures were for 10 min or until moderate nausea, whichever was sooner. The visual stimulus was a scene rotating in yaw at 0.2 Hz with superimposed "wobble". C-C was whole-body rotation on a turntable with eight 45° head tilts during each 30-s period. Control was head tilt without rotation. Rotational velocity was incremented in staircase steps of 3° · s−1 every 30 s. RESULTS: Groups were equivalent for Total Motion Sickness Symptom scores elicited by the first visual stimulus (combined: mean ± SD 10.8 ± 8.4). C-C produced greater Total Symptoms (20.3 ± 6.8) than Control (3.1 ± 3.7). Subjects recovered subjectively from C-C before retest of visual stimulus. For the retest visual stimulus, Total Symptoms were higher following C-C (15.1 ± 9.0) than following Control (8.3 ± 7.1) for both the 15 min and 2 h retests. Sickness ratings (SR) mirrored these effects of C-C. DISCUSSION: C-C motion sensitized subsequent responses to visual stimulation up to 2 h later. Sensitization of visual stimulation crossed modalities and appeared subconscious since it occurred despite subjective recovery from C-C. For some individuals, a previously relatively innocuous visual stimulus became nauseogenic on retest. The results have implications for the use of visual technologies within hours of exposure to provocative motion. Golding JF, Alund D, Gresty MA, Flynn MB. Sensitization of visually induced motion sickness by prior provocative physical motion. Aerosp Med Hum Perform. 2024; 95(10):741–748.

A Novel Online Position Estimation Method and Movement Sonification System: The Soniccup.

Existing methods to obtain position from inertial sensors typically use a combination of multiple sensors and orientation modeling; thus, obtaining position from a single inertial sensor is highly desirable given the decreased setup time and reduced complexity. The dead reckoning method is commonly chosen to obtain position from acceleration; however, when applied to upper limb tracking, the accuracy of position estimates are questionable, which limits feasibility. A new method of obtaining position estimates through the use of zero velocity updates is reported, using a commercial IMU, a push-to-make momentary switch, and a 3D printed object to house the sensors. The generated position estimates can subsequently be converted into sound through sonification to provide audio feedback on reaching movements for rehabilitation applications. An evaluation of the performance of the generated position estimates from a system labeled 'Soniccup' is presented through a comparison with the outputs from a Vicon Nexus system. The results indicate that for reaching movements below one second in duration, the Soniccup produces positional estimates with high similarity to the same movements captured through the Vicon system, corresponding to comparable audio output from the two systems. However, future work to improve the performance of longer-duration movements and reduce the system latency to produce real-time audio feedback is required to improve the acceptability of the system.

Enhancing postural balance assessment through neural network-based lower-limb muscle strength evaluation with reduced markers

Aiming to simplify the data acquisition process for balance diagnosis and focused on muscle, a direct factor affecting balance, to assess and judge postural stability. Utilizing a publicly available kinematic dataset, the research retained 3D coordinates and mechanical data for 8 markers on the lower limbs. By integrating this data with the musculoskeletal model in OpenSim, inverse kinematic calculations were performed to derive muscle forces. These forces, alongside the coordinates, were split into an 8:2 training and test set ratio. A neural network was then developed to predict muscle forces using normalized coordinate data from the training set as input, with corresponding muscle force data as training labels. The model’s accuracy was confirmed on the test set, achieving coefficients of determination ( R 2 ) above 0.99 for 276 muscle forces. Furthermore, the Force Maximum Percentage Difference (FMPD) was introduced as a novel criterion to evaluate and visualize lower limb balance, revealing significant discrepancies between the patient and control groups. This study successfully demonstrates that the neural network model can precisely predict lower limb muscle forces using reduced markers and introduces FMPD as an effective tool for assessing limb balance, providing a robust framework for future diagnostic and rehabilitative applications.