Bionic Training System A1: AI-Assisted Rehabilitation and Data-Driven Adaptivity

The Bionic Training System A1 is currently in the development phase as an advanced rehabilitation platform designed to support hand-related rehabilitation processes in hospital and clinical environments. The system is intended to assist in the practice and guidance of hand functions for individuals experiencing various forms of hand function loss, including situations arising from neurological conditions, injuries, or orthopedic procedures.

The platform uses bionic hand systems equipped with AI-assisted algorithms (Clinical Decision Support Systems, CDSS) and real-time sensor technologies. These components are being developed to explore the feasibility of adaptive training support, variable grip patterns, and responsive interaction based on user input. Through Natural Language Processing (NLP), the system also investigates the potential applicability of voice-controlled interfaces for future use.

Data-Driven Rehabilitation Concepts

By integrating Big Data analytics, the system investigates how continuous data processing and movement pattern analysis may contribute to the development of personalized training support. The platform is designed to provide insights into movement profiles, variations in training intensity, and progress indicators, with the aim of offering clinical teams additional information to support rehabilitation decision-making.

Three Supportive Training Modes (in development)

Passive Training – Supports guided finger movements such as flexion and extension, aimed at practicing motor patterns in a controlled environment.

Mirror Training – Utilizes monitored movements of the non-affected hand to support exercises for the affected side.

ADL-Focused Training – Targets activities related to daily living, supporting the practice of fine motor skills and functional hand movements.

Research Objectives

The integrated technologies of the Bionic Training System A1 are being investigated for usability, adaptivity, sensor performance, and data-processing characteristics.