MAHI Lab | Mechatronics and Haptic Interfaces Lab

We are developing an innovative approach to the control of robotic-assisted rehabilitation and other assistive devices.

We are interested in the effect of feedback on the rate and extent of motor skill learning and adaptation. Our intent is to apply the results of our investigations to the design of a more effective strategy for the rehabilitation of recovering stroke patients.

Mathematical Equations as Executable Models of Mechanical Systems

Incorporating simulation in vascular surgery education

Performance-based Adaptive Control of Robotic Rehabilitation and Assistive Devices

Autoworm

Role of Feedback

Long-term double integration of acceleration for position sensing and frequency domain system identification

Normalized movement quality measures for therapeutic robots strongly correlate with clinical motor impairment measures

Analysis and comparison of low cost gaming controllers for motion analysis

Expertise-Based Performance Measures in a Virtual Training Environment

Co-presentation of Force Cues for Skill Transfer via Shared-control Systems

Mechatronics and Haptic Interfaces Lab at Rice University