AUTOMATED MULTI-FEATURE SEGMENTATION OF TREADMILL RUNNING

The definition of gait events and phases have been well established in the literature through the use of qualitative movement descriptors. The repeatable, objective definitions of gait events and phases is the cornersone of sucess when performin a multi-center trial. A correlation-based multi-feature automated segmentation algorithm was developed and applied to treadmill running data. The features used were soley from 3D kinematic marker trajectory data, including generated features such as vectors between kinematic markers. The algorithm was compared against a trained tester who used visual inspection and threshold limits of the vGRF to segment stance. The automated segmentation approach was shown to consistently identify the same gait events as the trained tester, representing a significant time savings for the signal processing of large volume treadmill running data

Graceful User Following for Mobile Balance Assistive Robot in Daily Activities Assistance

Numerous diseases and aging can cause degeneration of people's balance ability resulting in limited mobility and even high risks of fall. Robotic technologies can provide more intensive rehabilitation exercises or be used as assistive devices to compensate for balance ability. However, With the new healthcare paradigm shifting from hospital care to home care, there is a gap in robotic systems that can provide care at home. This paper introduces Mobile Robotic Balance Assistant (MRBA), a compact and cost-effective balance assistive robot that can provide both rehabilitation training and activities of daily living (ADLs) assistance at home. A three degrees of freedom (3-DoF) robotic arm was designed to mimic the therapist arm function to provide balance assistance to the user. To minimize the interference to users' natural pelvis movements and gait patterns, the robot must have a Human-Robot Interface(HRI) that can detect user intention accurately and follow the user's movement smoothly and timely. Thus, a graceful user following control rule was proposed. The overall control architecture consists of two parts: an observer for human inputs estimation and an LQR-based controller with disturbance rejection. The proposed controller is validated in high-fidelity simulation with actual human trajectories, and the results successfully show the effectiveness of the method in different walking modes

Estimation of Physiological Tremor from Accelerometers for Real-Time Applications

Accurate filtering of physiological tremor is extremely important in robotics assisted surgical instruments and procedures. This paper focuses on developing single stage robust algorithms for accurate tremor filtering with accelerometers for real-time applications. Existing methods rely on estimating the tremor under the assumption that it has a single dominant frequency. Our time-frequency analysis on physiological tremor data revealed that tremor contains multiple dominant frequencies over the entire duration rather than a single dominant frequency. In this paper, the existing methods for tremor filtering are reviewed and two improved algorithms are presented. A comparative study is conducted on all the estimation methods with tremor data from microsurgeons and novice subjects under different conditions. Our results showed that the new improved algorithms performed better than the existing algorithms for tremor estimation. A procedure to separate the intended motion/drift from the tremor component is formulated

Design and implementation of modular robotic arm with active links

This thesis presents the design and implementation of a modular robot arm with scaleable number of degree of freedom (DOF). In our study, we have proposed the concept of Active Links as the basic unit of our manipulator.Master of Engineering (MPE