Wavelet Based Automated Postural Event Detection and Activity Classification with Single IMU (TEMPO)

Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person’s activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient’s home. In order to provide a lowcost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment - TEMPO. Using the TEMPO system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection and classification algorithm using denoised signals from single wireless inertial measurement unit (TEMPO) placed at sternum. The algorithm was further validated and verified with motion capture system in laboratory environment. Wavelet denoising highlighted postural events and transition durations that further provided clinical information on postural control and motor coordination. The presented method can be applied in real life ambulatory monitoring approaches for assessing condition of elderly

ASSISTIVE DEVICE FOR LOWER EXTREMITY GAIT TRAINING AND ASSISTANCE

Ph.DDOCTOR OF PHILOSOPH

Wright State University\u27s Celebration of Research, Scholarship and Creative Activities Book of Abstracts from Friday, April 21, 2017

The student abstract booklet is a compilation of abstracts from students\u27 oral and poster presentations at Wright State University\u27s Annual Celebration of Research, Scholarship and Creative Activities on April 21, 2017.https://corescholar.libraries.wright.edu/urop_celebration/1024/thumbnail.jp

A Systematic Review of Weight Perception in Virtual Reality: Techniques, Challenges, and Road Ahead

Weight is perceived through the combination of multiple sensory systems, and a wide range of factors – including touch, visual, and force senses – can influence the perception of heaviness. There have been remarkable advancements in the development of haptic interfaces throughout the years. However, a number of challenges limit the progression to enable humans to sense the weight in virtual reality (VR). This article presents an overview of the factors that influence how weight is perceived and the phenomenon that contributes to various types of weight illusions. A systematic review has been undertaken to assess the development of weight perception in VR, underlying haptic technology that renders the mass of a virtual object, and the creation of weight perception through pseudo-haptic. We summarize the approaches from the perspective of haptic and pseudo-haptic cues that exhibit the sense of weight such as force, skin deformation, vibration, inertia, control–display ratio, velocity, body gestures, and audio–visual representation. The design challenges are underlined, and research gaps are discussed, including accuracy and precision, weight discrimination, heavyweight rendering, and absolute weight simulation. This article is anticipated to aid in the development of more realistic weight perception in VR and stimulated new research interest in this topic

Design and Control of a Knee Exoskeleton for Assistance and Power Augmentation

Thanks to the technological advancements, assistive lower limb exoskeletons are moving from laboratory settings to daily life scenarios. This dissertation makes a contribution toward the development of assistive/power augmentation knee exoskeletons with an improved wearability, ergonomics and intuitive use. In particular, the design and the control of a novel knee exoskeleton system, the iT-Knee Bipedal System, is presented. It is composed by: a novel mechanism to transmit the assistance generated by the exoskeleton to the knee joint in a more ergonomic manner; a novel method that requires limited information to estimate online the torques experienced by the ankles, knees and hips of a person wearing the exoskeleton; a novel sensor system for shoes able to track the feet orientation and monitor their full contact wrench with the ground. In particular, the iT-Knee exoskeleton, the main component of the aforementioned system, is introduced. It is a novel six degree of freedom knee exoskeleton module with under-actuated kinematics, able to assist the flexion/extension motion of the knee while all the other joint\u2019s movements are accommodated. Thanks to its mechanism, the system: solves the problem of the alignment between the joint of the user and the exoskeleton; it automatically adjusts to different users\u2019 size; reduces the undesired forces and torques exchanged between the attachment points of its structure and the user\u2019s skin. From a control point of view, a novel approach to address difficulties arising in real life scenarios (i.e. noncyclic locomotion activity, unexpected terrain or unpredicted interactions with the surroundings) is presented. It is based on a method that estimates online the torques experienced by a person at his ankles, knees and hips with the major advantage that does not rely on any information of the user\u2019s upper body (i.e. pose, weight and center of mass location) or on any interaction of the user\u2019s upper body with the environment (i.e. payload handling or pushing and pulling task). This is achieved v by monitoring the full contact wrench of the subject with the ground and applying an inverse dynamic approach to the lower body segments. To track the full contact wrench between the subject\u2019s feet and the ground, a novel add on system for shoes has been developed. The iT-Shoe is adjustable to different user\u2019s size and accommodates the plantar flexion of the foot. It tracks the interactions and the orientation of the foot thanks to two 6axis Force/Torque sensors, developed in-house, with dedicated embedded MEMS IMUs placed at the toe and heel area. Different tasks and ground conditions were tested to validate and highlight the potentiality of the proposed knee exoskeleton system. The experimental results obtained and the feedback collected confirm the validity of the research conducted toward the design of more ergonomic and intuitive to use exoskeletons