SENSOR METHODS FOR BIOMECHANICAL PARAMETER ACQUISITION IN MOBILE TREATMENT AND REHABILITATION SYSTEMS

The paper addresses sensor selection for mobile treatment and rehabilitation systems under constraints on device weight, energy consumption, computing resources, and patient burden. The objective is to systematize methods for acquiring biomechanical parameters and to establish a methodological framework for selecting a minimally sufficient multimodal sensor configuration for a specified clinical task. Based on the reviewed literature, inertial measurement units, surface electromyography, pressure and force sensors, flexible strain sensors, goniometers, and markerless computer-vision methods are compared with respect to their information content, advantages, and limitations. A configuration is represented by the sensor set, anatomical placement, sampling frequencies, and processing algorithms, while its performance is assessed through measurement error, latency, energy use, computational cost, and patient burden. A procedure is proposed that starts with full multimodal acquisition and proceeds through sensor ablation, sampling-rate reduction, non-inferiority assessment, and multi-criteria selection. Metrics for subsequent experimental validation cover agreement with laboratory reference systems, measurement reliability, clinical relevance, and operational usability. The methodological outcome is not a universal hardware configuration but a principled way of identifying the sensor set required for a specific rehabilitation context of use. The proposed framework may support resource-efficient mobile biomechanical monitoring; experimental validation of the approach remains future work.