Bionic Training System Z2

The Bionic Training System Z2 is currently in the development phase as an advanced rehabilitation concept that integrates Soft Robotic Exoskeleton Technology with AI-supported data analytics. The system is designed to support hand-related rehabilitation processes within research and clinical development environments.

The bionic hand systems utilize AI-based Clinical Decision Support System (CDSS) algorithms and real-time sensor technologies to explore the feasibility of adaptive movement assistance, 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.

AI and Big Data for Supportive Rehabilitation Concepts

The Z2 system collects and processes real-time motion and interaction data. Using artificial intelligence (AI) and big data analysis, it explores how user movement patterns can contribute to:
– analyzing motion profiles,
– adjusting training parameters,
– generating additional insights for clinical teams supporting rehabilitation processes.

(Note: Some functionalities are still under investigation within an R&D context.)

Supportive Training Modes

Passive Training – Supports controlled finger movements such as flexion and extension to practice motor patterns.
Assistance Training – Explores how the system can support users during shared or partially assisted movements.
Mirror Training – Uses controlled movements of the unaffected hand to support exercises for the affected hand in a controlled research environment.
Interactive Training Modes – Conceptual modes aimed at stimulating exercise through game-based or interactive interfaces.

Research Objectives

The integrated technologies of the Bionic Training System Z2 are being evaluated with respect to:
– sensor performance,
– data processing capabilities,
– adaptive algorithms for motion analysis,
– technical usability and system responsiveness.