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. • A co-design approach ensuring holistic development of a novel rehabilitation tool. • Gamification boosts engagement, attention, and motivation during therapy sessions. • Data from instrumented bricks trains AI to detect rehabilitation events in real time. • Collects cognitive and motor data to enable personalized rehabilitation plans.

Freezing of gait (FoG) is a walking disturbance in the Parkinson's disease (PD). The freezing ratio (FoG-ratio) is a parameter used to quantify overall freezing severity rather than to assess single freezing episodes. Originally the FoG-ratio was designed to be computed from lower limb acceleration. However, some available measurement systems get their data from a single sensor located elsewhere, e.g. on the lower back. The objective of our paper is to analyse whether acceleration signals measured on different body locations result in a consistent FoG-ratio. Eighty-four people with PD and 65 people without neurological disorders completed an instrumented Timed Up&Go Test (iTUG) twice. The FoG-ratios from inertial units placed on the chest, lower back, left and right lower limbs were calculated. There were significant differences between the tested FoG-ratios in the control group as well as in the PD group for both segments. Four significant, but not consistent, correlations were revealed for the turn segment in the PD group. Eight correlations were revealed in the control group. The inter-trial reliability of all the tested cases for gait was good (rho>0.75) but only in one case for turning. In conclusion, the placement of sensors affected the FoG-ratio parameter output. The different FoG-ratios reflect different amounts of power in the locomotion band of body segments. This could result in inconclusive validity and incomparability of freezing severity presented in studies when the sensor is placed somewhere other than on the lower limbs. • The freezing ratio (FoG-ratio) was developed to quantify overall freezing severity. • The FoG-ratio was designed to be computed from lower limb acceleration. • FoG-ratios from other body locations differ from lower limb FoG-ratio during turn.

BackgroundAt equivalent speeds, above-knee amputee subjects have a higher metabolic cost than non-amputees. Following amputation, the ankle propulsion is reduced, and using other joints to compensate is mechanically less efficient. ObjectiveThis study investigated the link between mechanical work and metabolic cost in abled-bodied subjects using a prosthesis simulator, and the influence of foot energy restitution by comparing a foot with restitution to one without. MethodSix volunteers fitted with an orthosis immobilising their ankle and knee, enabling the use of a prosthesis, carried out a gait analysis and an analysis of metabolic cost. The total lower limb mechanical work and works at the hip, knee and ankle were computed. ResultsWith an almost twofold increase, metabolic cost and hip work were significantly higher in both configurations with prosthesis than without (p < 0.001 for both variables in both configurations), while total lower limb mechanical work showed no significant difference between configurations. No significant difference was observed between the two prosthetic feet in terms of metabolic cost nor mechanical work performed by the subject. DiscussionTotal lower limb mechanical work alone cannot explain the extra metabolic cost in subjects fitted with a knee-foot prosthesis simulator; internal inefficiencies exist. We also found that metabolic cost and hip work increase and decrease simultaneously, thus studying hip muscles work could be interesting. With no significant difference between the two feet, optimising ankle propulsion seems to be ineffective in improving metabolic cost. These findings should be evaluated in a sample of above-knee amputee subjects.