This paper presents a therapeutic serious game integrating a commercial connected toy (LEGO Mario) to improve motor rehabilitation for children with cerebral palsy with unilateral upper limb disorder. By combining real-time sensor data, Bluetooth communication, a dynamic difficulty adjustment system implemented in Unreal Engine, and a progression system using pixel art as a motivation lever, the project offers a novel approach to maintaining engagement and personalizing rehabilitation. The research follows a clinically inspired methodology and introduces game prototypes validated by healthcare professionals and designed to be adaptable to individual patient profiles. The results show promising effects on engagement and motor participation.

CPLAY is a novel serious-game platform combining miniaturized, instrumented building bricks with a tablet interface and AI-driven activity recognition to deliver personalized, gamified upper-limb rehabilitation for children with Developmental Coordination Disorder or Cerebral Palsy. Developed through a co-design process with therapists, engineers, parents and children, two IMU-equipped brick form factors transmit 70 Hz motion data via Bluetooth to a tablet hosting fifteen progressively challenging 3D assembly tasks enriched with rewards and audiovisual feedback. In a clinical feasibility trial, 30 children (mean age 9.1 +/- 1.0 years) performed each model twice under supervision; synchronized motion and video data were annotated to train signal-processing routines and deep-learning classifiers. Signal processing detected all 36 movement and fall events (one false positive), while the Transformer model outperformed other approaches, achieving 86.0% multi-class accuracy and 85-96% binary accuracy across activity labels. These results demonstrate CPLAY's ability to objectively detect and classify key rehabilitation movements, paving the way for adaptive, AI-driven therapy, with future work focused on embedding a recommendation engine, scaling trials and refining AI models. (c) 2025 AGBM. Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Background The assessment of gait disorders in patients with neuromotor conditions, such as cerebral palsy (CP), has been a focus of clinical and research attention, with electromyography (EMG) offering a nuanced understanding of neurological and neuromuscular disorders. However, the interpretation of EMG data in the context of gait analysis remains challenging due to the complexity of neuromotor dynamics and variability in assessment methodologies. Research question To which consensus can we get in a group of experts in the fields of neurological and neuromuscular disorders, biomechanics, and clinical gait analysis to establish standardized protocols and a common language for the measurement and analysis of EMG data in gait disorders, particularly in people living with CP? Methods A three-round Delphi process was conducted from February to September 2023 to gather opinions of 53 experts on the use of surface EMG data during gait in the context of CP. The surveys were conducted using the tool 'SoSci Survey' with a focus on free-text answers. Results The experts agreed on the usefulness of EMG data, but a consensus on specific clinical decisions involving EMG could not be reached. Additionally, the study provides a terminological framework for EMG evaluation during gait and a comprehensive list of practical problems and solutions, when evaluating EMG data. The study indicates that, despite a general community consensus on the ideal approaches to data processing and evaluation, these methods are not commonly implemented in a standardized manner. Both raw and enveloped data are widely used in clinical routines, however, the protocol for generating normative data lacks consistency across gait laboratories. Significance The study suggests that while there may be differences in the way EMG data is analyzed, there is a shared understanding of the key features that are relevant for gait analysis.

Spasticity might affect gait in children with cerebral palsy. Quantifying its occurrence during locomotion is challenging. One approach is to determine kinematic stretch reflex thresholds, usually on the velocity, during passive assessment and to search for their exceedance during gait. These thresholds are determined through EMG-Onset detection algorithms, which are variable in performance and sensitive to noisy data, and can therefore lack consistency. This study aimed to evaluate the feasibility of determining the velocity stretch reflex threshold from maximal musculotendon acceleration. Eighteen children with CP were recruited and underwent clinical gait analysis and a full instrumented assessment of their soleus, gastrocnemius lateralis, semitendinosus, and rectus femoris spasticity, with EMG, kinematics, and applied forces being measured simultaneously. Using a subject-scaled musculoskeletal model, the acceleration-based stretch reflex velocity thresholds were determined and compared to those based on EMG-Onset determination. Their consistencies according to physiological criteria, i.e., if the timing of the threshold was between the beginning of the stretch and the spastic catch, were evaluated. Finally, two parameters designed to evaluate the occurrence of spasticity during gait, i.e., the proportion of the gait trial time with a gait velocity above the velocity threshold and the number of times the threshold was exceeded, were compared. The proposed method produces velocity stretch reflex thresholds close to the EMG-based ones. For all muscles, no statistical difference was found between the two parameters designed to evaluate the occurrence of spasticity during gait. Contrarily to the EMG-based methods, the proposed method always provides physiologically consistent values, with median electromechanical delays of between 50 and 130 ms. For all subjects, the semitendinosus velocity during gait usually exceeded its stretch reflex threshold, while it was less frequent for the three other muscles. We conclude that a velocity stretch reflex threshold, based on musculotendon acceleration, is a reliable substitute for EMG-based ones.

Inter-segmental moments come from muscles contractions, but also from passive moments, resulting from the resistance of the periarticular structures. To quantify the passive contribution of uni- and biarticular structures during gait, we propose an innovative procedure and model. 12 typically developed (TD) children and 17 with cerebral palsy (CP) participated in a passive testing protocol. The relaxed lower limb joints were manipulated through full ranges of motion while kinematics and applied forces were simultaneously measured. The relationships between uni-/biarticular passive moments/forces and joint angles/musculo-tendon lengths were modelled by a set of exponential functions. Then, subject specific gait joint angles/musculo-tendon lengths were input into the determined passive models to estimate joint moments and power attributable to passive structures. We found that passive mechanisms contribute substantially in both populations, mainly during push-off and swing phases for hip and knee and push-off for the ankle, with a distinction between uni- and biarticular structures. CP children showed comparable passive mechanisms but larger variability than the TD ones and higher contributions. The proposed procedure and model enable a comprehensive assessment of the passive mechanisms for a subject-specific treatment of the stiffness implying gait disorders by targeting when and how passive forces are impacting gait.

Joint resistance to passive mobilization has already been estimated in-vivo in several studies by measuring the applied forces and moments while manipulating the joint. Nevertheless, in most of the studies, simplified modelling approaches are used to calculate this joint resistance. The impact of these simplifications is still unknown. We propose a protocol that enables a reference 3D inverse dynamics approach to be implemented and compared to common simplified approaches. Eight typically developed children and eight children with cerebral palsy were recruited and underwent a passive testing protocol, while applied forces and moments were measured through a 3D handheld dynamometer, simultaneously to its 3D kinematics and the 3D kinematics of the different segments. Then, passive joint resistance was estimated using the reference 3D inverse dynamics approach and according to 5 simplified approaches found in the literature, i.e. ignoring either the dynamometer kinematics, the measured moments alone or together with the measured tangential forces, the gravity and the inertia of the different segments, or the distal segments kinematics. These simplifications lead to non-negligible differences with respect to the reference 3D inverse dynamics, from 3 to 32% for the ankle, 4 to 34% for the knee and 1 to 58% for the hip depending of the different simplifications. Finally, we recommend a complete 3D kinematics and dynamics modelling to estimate the joint resistance to passive mobilization.

Introduction In paediatric rehabilitation, fun and motivation are also critical keys to successful therapy. A variety of interventions have shown positive effects, high level of interest, compliance and engagement with active video game (AVG). This seems to be an interesting approach for the postoperative gait rehabilitation of children with cerebral palsy (CP). In this study, we will investigate if an overground gait training (GT) delivered through an AVG can improve walking capacity and anaerobic performance. Methods and analysis This study is a randomised clinical controlled trial. A total of 14 children and adolescents in the age of 10–18 years with CP will be included. The minimum time between surgery and inclusion will be 7 weeks. The test group will participate in the GT programme with Augmented Reality Rehabilitation of Walking-Cerebral Palsy AVG, control group will receive GT on a treadmill. The primary outcome is the 6-Min Walk Test assessing walking capacity; secondary outcomes are the Muscle Power Sprint Test for anaerobic performance and Shuttle Run Test for physical fitness level. Satisfaction is tested with the Physical Activity Enjoyment Scale. Ethics and dissemination The findings will be disseminated by publications in peer-reviewed journals and conferences. This study received agreement from French ethic committee (Comité de Protection des Personnes Sud-Est VI—Number 2020-A02959-30). Trial registration number NCT04837105.

This article details the design of a co-created, evidence-based biofeedback therapy game addressing the research question: is the biofeedback implementation efficient, effective, and engaging for promoting quality movement during a therapy game focused on hand gestures? First, we engaged nine young people with Cerebral Palsy (CP) as design partners to co-create the biofeedback implementation. A commercially available, tap-controlled game was converted into a gesture-controlled game with added biofeedback. The game is controlled by forearm electromyography and inertial sensors. Changes required to integrate biofeedback are described in detail and highlight the importance of closely linking movement quality to short- and long-term game rewards. After development, 19 participants (8-17 years old) with CP played the game at home for 4 weeks. Participants played 17 +/- 9 min/day, 4 +/- 1 day/week. The biofeedback implementation proved efficient (i.e. participants reduced compensatory arm movements by 10.2 +/- 4.0%), effective (i.e. participants made higher quality gestures over time), and engaging (i.e. participants consistently chose to review biofeedback). Participants found the game usable and enjoyable. Biofeedback design in therapy games should consider principles of motor learning, best practices in video game design, and user perspectives. Design recommendations for integrating biofeedback into therapy games are compiled in an infographic to support interdisciplinary knowledge sharing.

AbstractThis review sought to describe and analyze published protocols for rehabilitation after single-event multilevel surgery for people with cerebral palsy, to identify their differences and limits, and to introduce a common step-by-step framework for future descriptions and assessments of postoperative rehabilitation protocols.The MEDLINE, Embase, CINAHL, and the Cochrane Library databases were searched. Inclusion criteria were as follows: (1) single-event multilevel surgery, (2) full-text reports published after 1985, and (3) articles with a method section describing the rehabilitation protocol. Interventions were coded using the Oxford Levels of Evidence and the Methodological Index for Non-Randomized Studies Index.Twenty-four articles were included in the review. Studies included patients aged 4–30 yrs with spastic cerebral palsy (hemiplegia, diplegia, and quadriplegia). The mean postoperative rehabilitation duration was 4.5 mos, with 4 sessions per week, and rehabilitation took place in a rehabilitation center. This review provides relevant information about the modalities, contents, limits, and difficulties associated with the post-SEMS rehabilitation protocol reported in the literature. Pain was identified as a major problem.A more precise and comprehensive description of post-SEMS rehabilitation protocols would be useful. The proposed five-step framework could be used by future studies to standardize their protocol description in terms of objective, content, and intensity.

In an augmented reality environment, the range of possible real-time visual feedback is extensive. This study aimed to compare the impact of six scenarios in augmented reality combining four visual feedback characteristics on achieving a target walking speed. The six scenarios have been developed for Microsoft Hololens augmented reality headset. The four feedback characteristics that we have varied were: Color; Spatial anchoring; Speed of the feedback, and Persistence. Each characteristic could have different values (for example, the color could be unicolor, bicolor, or gradient). Participants had to walk for two consecutive walking trials for each scenario: at their maximal speed and an intermediate speed. Mean speed, percentage of time spent above or around target speed, and time to reach target speed were compared between scenarios using mixed linear models. A total of 25 children with disabilities have been included. The feasibility and user experience were excellent. Mean speed during scenario 6, which displayed feedback with gradient color, attached to the world, with a speed relative to the player equal to his speed, and that disappeared over time, was significantly higher than other scenarios and control (p =0.003). Participants spent 80.98% of time above target speed during scenario 6. This scenario mixed the best combination of feedback characteristics to exceed the target walking speed (p=0.0058). Scenarios 5 and 6, which shared the same feedback characteristics for spatial anchoring (world-locked) and feedback speed (equal to the player speed), decreased the time to reach the target speed (p=0.019). Delivering multi-modal feedback has been recognized as more effective for improving motor performance. Therefore, our results showed that not all visual feedback had the same impact on performance. Further studies are required to test the weight of each feedback characteristic and their possible interactions inside each scenario. This study was registered in the ClinicalTrials.gov database (NCT04460833).

Serious games are a promising approach to improve gait rehabilitation for people with gait disorders. Combined with wearable augmented reality headset, serious games for gait rehabilitation in a clinical setting can be envisaged, allowing to evolve in a real environment and provide fun and feedback to enhance patient's motivation. This requires a method to obtain accurate information on the spatiotemporal gait parameters of the playing patient. To this end, we propose a new algorithm called HoloStep that computes spatiotemporal gait parameters using only the head pose provided by an augmented reality headset (Hololens). It is based on the detection of peaks associated to initial contact event, and uses a combination of locking distance, locking time, peak amplitude detection with custom thresholds for children with CP. The performance of HoloStep was compared during a walking session at comfortable speed to Zeni's reference algorithm, which is based on kinematics and a full 3D motion capture system. Our study included 62 children with cerebral palsy (CP), classified according to Gross Motor Function Classification System (GMFCS) between levels I and III, and 13 healthy participants (HP). Metrics such as sensitivity, specificity, accuracy and precision for step detection with HoloStep were above 96%. The Intra-Class Coefficient between steps length calculated with HoloStep and the reference was 0.92 (GMFCS I), 0.86 (GMFCS II/III) and 0.78 (HP). HoloStep demonstrated good performance when applied to a wide range of gait patterns, including children with CP using walking aids. Findings provide important insights for future gait intervention using augmented reality games for children with CP.

Inter-segmental moments computed by inverse dynamic during gait come from active moments, due to muscle contraction, but also from passive moments, resulting from the resistance of the periarticular structures to their deformation. The evaluation of the proportion of the inter-segmental moments that can be attributed to passive moments has led to divergent results. Thus, the purpose of this study was to systematically search and synthesize the evidence of the contribution of passive moments to inter-segmental moments during healthy and pathological gait. A broad systematic search was performed including four databases. Thirteen studies met all inclusion criteria. Results showed that passive moments participate to inter-segmental moments during gait in a non-negligible way. For the ankle, the evaluation of the proportion of inter-segmental moment attributed to passive structures is 5-20% around the push-off. For the knee, this proportion is 40-98% during late swing and 10-80% during the single support phase. For the hip, it is 20-50% at push-off. For pathological population, it has been shown that this contribution may sometimes be more important, either due to a smaller inter-segmental moment or a larger passive moment. These results suggest that passive mechanisms can contribute substantially to normal human gait, facilitating the propulsion or the braking of the joint. Passive structures, acting as elastic springs, thus help to reduce the energy cost of gait. For pathological gait, studying the contribution of passive moments to inter-segmental moments can help to better understand the aetiology of the pathology. (c) 2021 Elsevier Ltd. All rights reserved.

Movement-based video games can provide engaging practice for repetitive therapeutic gestures towards improving manual ability in youth with cerebral palsy (CP).However, home-based gesture calibration and classification is needed to personalize therapy and ensure an optimal challenge point.Nineteen youth with CP controlled a video game during a 4-week home-based intervention using therapeutic hand gestures detected via electromyography and inertial sensors.The in-game calibration and classification procedure selects the most discriminating, person-specific features using random forest classification.Then, a support vector machine is trained with this feature subset for in-game interaction.The procedure uses features intended to be sensitive to signs of CP and leverages directional statistics to characterize muscle activity around the forearm.Homebased calibration showed good agreement with video verified ground truths (0.86 ± 0.11, 95%CI = 0.93-0.97).Across participants, classifier performance (F1-score) for the primary therapeutic gesture was 0.90 ± 0.05 (95%CI = 0.87-0.92)and, for the secondary gesture, 0.82 ± 0.09 (95%CI = 0.77-0.86).Features sensitive to signs of CP were significant contributors to classification and correlated to wrist extension improvement and increased practice time.This study contributes insights for classifying gestures in people with CP and demonstrates a new gesture controller to facilitate home-based therapy gaming.

Introduction. Serious games (SG) combined with virtual or augmented reality technologies are used to improve gait parameters for children with cerebral palsy (CP)1,2 We have developed a SG using the Microsoft Hololens augmented reality headset called ARRoW-CP, which integrates motor learning theories3 and audio-visual feedback4 to perform a 4-week intensive overground gait training (OGT) for children with CP. Methods. This work followed the development framework PROGame5 within a multidisciplinary team. Regular user tests with therapists and patients were conducted to be as close as possible to their needs. Key steps of the project included: 1. A validity study of the algorithm measuring spatiotemporal gait parameters with the AR headset6 2. An experimental study to determine the best combination of feedback modalities to achieve maximum walking speed (WS)7 3. A randomized control trial (in progress) including children with CP. They participate in a four-week OGT with ARRoW-CP vs. treadmill training.8,9 Outcomes are the 6-minutes-walk test and the Muscle-Power-Sprint-Test, which assess functional capacity and anaerobic performance. Results. First qualitative results (N=5) show a significant improvement for 6MWT and MPST. Enjoyment and motivation are higher in the ARRoW-CP group. Children present a linear progression in WS between each session and weeks. Discussion and Conclusion. ARRoW-CP combines multiple ingredients of motor learning theories3: context focused therapy, goal-directed training,10 task-specific, variable practice, high intensity, feedback during therapy sessions and motivation of the patient.11 Preliminary results are very positive, we plan to include 40 patients to test our rehabilitation programme and the benefits of our SG. 1. Lopes S, Magalhaes P, Pereira A, et al. Games Used With Serious Purposes: A Systematic Review of Interventions in Patients With Cerebral Palsy. Frontiers in Psychology. 2018;9(1712). doi:10.3389/fpsyg.2018.01712 2. Cho C, Hwang W, Hwang S, Chung Y. Treadmill Training with Virtual Reality Improves Gait, Balance, and Muscle Strength in Children with Cerebral Palsy. The Tohoku Journal of Experimental Medicine. 2016;238(3):213-218. doi:10.1620/tjem.238.213 3. Demers M, Fung K, Subramanian S, Lemay M, Robert M. Do virtual interventions in individuals with cerebral palsy make use of motor learning principles?: A systematic review (Preprint). JMIR Serious Games. Published online August 25, 2020. doi:10.2196/23822 4. Sigrist R, Rauter G, Riener R, Wolf P. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychon Bull Rev. 2013;20(1):21-53. doi:10.3758/s13423-012-0333-8 5. Amengual Alcover E, Jaume-i-Capo A, Moya-Alcover B. PROGame: A process framework for serious game development for motor rehabilitation therapy. Martinuzzi A, ed. PLOS ONE. 2018;13(5):e0197383. doi:10.1371/journal.pone.0197383 6. Guinet A-L, Bouyer G, Otmane S, Desailly E. Validity of Hololens Augmented Reality Head Mounted Display for Measuring Gait Parameters in Healthy Adults and Children With Cerebral Palsy. Sensors (Basel, Switzerland). 2021;21:2697. doi:10.3390/s21082697 7. Guinet AL, Biddiss E, Khan A, et al. Towards an AR game for walking rehabilitation: Preliminary study of the impact of augmented feedback modalities on walking speed. IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct). Published online 2020. 8. Zwinkels M, Verschuren O, de Groot JF, et al. Effects of High-Intensity Interval Training on Fitness and Health in Youth With Physical Disabilities: Pediatric Physical Therapy. 2019;31(1):84-93. doi:10.1097/PEP.0000000000000560 9. Grecco LAC, de Freitas TB, Satie J, Bagne E, Oliveira CS, de Souza DR. Treadmill training following orthopedic surgery in lower limbs of children with cerebral palsy. Pediatr Phys Ther. 2013;25(2):187-192; discussion 193. doi:10.1097/PEP.0b013e3182888495 10. Novak I, Morgan C, Fahey M, et al. State of the Evidence Traffic Lights 2019: Systematic Review of Interventions for Preventing and Treating Children with Cerebral Palsy. Curr Neurol Neurosci Rep. 2020;20(2):3. doi:10.1007/s11910-020-1022-z 11. Cano-de-la-Cuerda R, Molero-Sanchez A, Carratala-Tejada M, et al. Theories and control models and motor learning: Clinical applications in neurorehabilitation. Neurologia (English Edition). 2015;30(1):32-41. doi:10.1016/j.nrleng.2011.12.012