Lessons in Using Vibrotactile Feedback to Guide Fast Arm Motions

We present and evaluate an arm-motion guidance system that uses magnetic tracking sensors and low cost vibrotactile actuators. The system measures the movement of the user’s arm and provides vibration feedback at the wrist and elbow when they stray from the desired motion. An initial study was conducted to investigate whether adding tactile feedback to visual feedback reduces motion errors when a user is learning a new arm trajectory. Although subjects preferred it, we found that the addition of tactile feedback did not affect motion tracking performance. We also found no strong preference or performance differences between attractive and repulsive tactile feedback. Some factors that may have influenced these results include the speed and the complexity of the tested motions, the type of tactile actuators and drive signals used, and inconsistencies in joint angle estimation due to Euler angle gimbal lock. We discuss insights from this analysis and provide suggestions for future systems and studies in tactile motion guidance

Scalability of the Size of Patterns Drawn Using Tactile Hand Guidance

Haptic feedback for handwriting training has been extensively studied, but with primary focus on kinematic feedback. We provide vibrotactile feedback through a wrist worn sleeve to guide the user to recreate unknown patterns and study the impact of vibrational duration (1, 2, 3 seconds) on pattern scaling. User traces a line at 90° angles, while attempting to maintain a constant speed, in the direction of the motor activated till a different motor activation is perceived. Shape and size are two features of good letter formation. Study performed on three subjects showed the ability to utilize four vibrotactile motors to guide the hand towards correct shape formation with high accuracy (\u3e 95%). The overall size of the letter was observed to scale linearly with the vibrational duration. Implications for utilizing the vibrational feedback for handwriting correction are discussed

Assisting Human Motion-Tasks with Minimal, Real-time Feedback

Teaching physical motions such as riding, exercising, swimming, etc. to human beings is hard. Coaches face difficulties in communicating their feedback verbally and cannot correct the student mid-action; teaching videos are two dimensional and suffer from perspective distortion. Systems that track a user and provide him real-time feedback have many potential applications: as an aid to the visually challenged, improving rehabilitation, improving exercise routines such as weight training or yoga, teaching new motion tasks, synchronizing motions of multiple actors, etc. It is not easy to deliver real-time feedback in a way that is easy to interpret, yet unobtrusive enough to not distract the user from the motion task. I have developed motion feedback systems that provide real-time feedback to achieve or improve human motion tasks. These systems track the user\u27s actions with simple sensors, and use tiny vibration motors as feedback devices. Vibration motors provide feedback that is both intuitive and minimally intrusive. My systems\u27 designs are simple, flexible, and extensible to large-scale, full-body motion tasks. The systems that I developed as part of this thesis address two classes of motion tasks: configuration tasks and trajectory tasks. Configuration tasks guide the user to a target configuration. My systems for configuration tasks use a motion-capture system to track the user. Configuration-task systems restrict the user\u27s motions to a set of motion primitives, and guide the user to the target configuration by executing a sequence of motion-primitives. Trajectory tasks assume that the user understands the motion task. The systems for trajectory tasks provide corrective feedback that assists the user in improving their performance. This thesis presents the design, implementation, and results of user experiments with the prototype systems I have developed

Multimodal “sensory illusions” for improving spatial awareness in virtual environments

Inaccurate judgement of distances in virtual environments (VEs) restricts their usefulness for engineering development, in which engineers must have a good understanding of the spaces they are designing. Multimodal feedback can improve depth perception in VEs, but this has yet to be implemented and tested in engineering applications with systems which provide haptic feedback to the body. The project reported in this paper will develop a multimodal VE to improve engineers’ understanding of 3D spaces. It will test the concept of “sensory illusions” where the point of collision in the VE differs to the point of haptic feedback on the body. This will permit the use of fewer vibrotactile devices and therefore the development of a more wearable system. This paper describes related work in multisensory and tactile stimulation which suggests that our perception of a stimulus is not fixed to the point of contact

Doctor of Philosophy

dissertationWhen interacting with objects, humans utilize their sense of touch to provide information about the object and surroundings. However, in video games, virtual reality, and training exercises, humans do not always have information available through the sense of touch. Several types of haptic feedback devices have been created to provide touch information in these scenarios. This dissertation describes the use of tactile skin stretch feedback to provide cues that convey direction information to a user. The direction cues can be used to guide a user or provide information about the environment. The tactile skin stretch feedback devices described herein provide feedback directly to the hands, just as in many real life interactions involving the sense of touch. The devices utilize a moving tactor (actuated skin contact surface, also called a contactor) and surrounding material to give the user a sense of the relative motion. Several game controller prototypes with skin stretch feedback embedded into the device to interface with the fingers were constructed. Experiments were conducted to evaluate user performance in moving the joysticks to match the direction of the stimulus. These experiments investigated stimulus masking effects with both skin stretch feedback and vibrotactile feedback. A controller with feedback on the thumb joysticks was found to have higher user accuracy. Next, precision grip and power grip skin stretch feedback devices were created to investigate cues to convey motion in a three-dimensional space. Experiments were conducted to compare the two devices and to explore user accuracy in identifying different direction cue types. The precision grip device was found to be superior in communicating direction cues to users in four degrees of freedom. Finally, closed-loop control was implemented to guide users to a specific location and orientation within a three-dimensional space. Experiments were conducted to improve controller feedback which in turn improved user performance. Experiments were also conducted to investigate the feasibility of providing multiple cues in succession, in order to guide a user with multiple motions of the hand. It was found that users can successfully reach multiple target locations and orientations in succession

Reaching Performance in Heathy Individuals and Stroke Survivors Improves after Practice with Vibrotactile State Feedback

Stroke causes deficits of cognition, motor, and/or somatosensory functions. These deficits degrade the capability to perform activities of daily living (ADLs). Many research investigations have focused on mitigating the motor deficits of stroke through motor rehabilitation. However, somatosensory deficits are common and may contribute importantly to impairments in the control of functional arm movement. This dissertation advances the goal of promoting functional motor recovery after stroke by investigating the use of a vibrotactile feedback (VTF) body-machine interface (BMI). The VTF BMI is intended to improve control of the contralesional arm of stroke survivors by delivering supplemental limb-state feedback to the ipsilesional arm, where somatosensory feedback remains intact. To develop and utilize a VTF BMI, we first investigated how vibrotactile stimuli delivered on the arm are perceived and discriminated. We determined that stimuli are better perceived sequentially than those delivered simultaneously. Such stimuli can propagate up to 8 cm from the delivery site, so future applications should consider adequate spacing between stimulation sites. We applied these findings to create a multi-channel VTF interface to guide the arm in the absence of vision. In healthy people, we found that short-term practice, less than 2.5 hrs, allows for small improvements in the accuracy of horizontal planar reaching. Long-term practice, about 10 hrs, engages motor learning such that the accuracy and efficiency of reaching is improved and cognitive loading of VTF-guided reaching is reduced. During practice, participants adopted a movement strategy whereby BMI feedback changed in just one channel at a time. From this observation, we sought to develop a practice paradigm that might improve stroke survivors’ learning of VTF-guided reaching without vision. We investigated the effects of practice methods (whole practice vs part practice) in stroke survivors’ capability to make VTF-guided arm movements. Stroke survivors were able to improve the accuracy of VTF-guided reaching with practice, however there was no inherent differences between practice methods. In conclusion, practice on VTF-guided 2D reaching can be used by healthy people and stroke survivors. Future studies should investigate long-term practice in stroke survivors and their capability to use VTF BMIs to improve performance of unconstrained actions, including ADLs

A Person-Centric Design Framework for At-Home Motor Learning in Serious Games

abstract: In motor learning, real-time multi-modal feedback is a critical element in guided training. Serious games have been introduced as a platform for at-home motor training due to their highly interactive and multi-modal nature. This dissertation explores the design of a multimodal environment for at-home training in which an autonomous system observes and guides the user in the place of a live trainer, providing real-time assessment, feedback and difficulty adaptation as the subject masters a motor skill. After an in-depth review of the latest solutions in this field, this dissertation proposes a person-centric approach to the design of this environment, in contrast to the standard techniques implemented in related work, to address many of the limitations of these approaches. The unique advantages and restrictions of this approach are presented in the form of a case study in which a system entitled the "Autonomous Training Assistant" consisting of both hardware and software for guided at-home motor learning is designed and adapted for a specific individual and trainer. In this work, the design of an autonomous motor learning environment is approached from three areas: motor assessment, multimodal feedback, and serious game design. For motor assessment, a 3-dimensional assessment framework is proposed which comprises of 2 spatial (posture, progression) and 1 temporal (pacing) domains of real-time motor assessment. For multimodal feedback, a rod-shaped device called the "Intelligent Stick" is combined with an audio-visual interface to provide feedback to the subject in three domains (audio, visual, haptic). Feedback domains are mapped to modalities and feedback is provided whenever the user's performance deviates from the ideal performance level by an adaptive threshold. Approaches for multi-modal integration and feedback fading are discussed. Finally, a novel approach for stealth adaptation in serious game design is presented. This approach allows serious games to incorporate motor tasks in a more natural way, facilitating self-assessment by the subject. An evaluation of three different stealth adaptation approaches are presented and evaluated using the flow-state ratio metric. The dissertation concludes with directions for future work in the integration of stealth adaptation techniques across the field of exergames.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Multimodal "Sensory Illusions" for Improving Spatial Awareness in Virtual Environments

Inaccurate judgement of distances in virtual environments (VEs) restricts their usefulness for engineering development, in which engineers must have a good understanding of the spaces they are designing. Multimodal feedback can improve depth perception in VEs, but this has yet to be implemented and tested in engineering applications with systems which provide haptic feedback to the body. The project reported in this paper will develop a multimodal VE to improve engineers’ understanding of 3D spaces. It will test the concept of “sensory illusions” where the point of collision in the VE differs to the point of haptic feedback on the body. This will permit the use of fewer vibrotactile devices and therefore the development of a more wearable system. This paper describes related work in multisensory and tactile stimulation which suggests that our perception of a stimulus is not fixed to the point of contact

Vibrotactile Sensory Augmentation and Machine Learning Based Approaches for Balance Rehabilitation

Vestibular disorders and aging can negatively impact balance performance. Currently, the most effective approach for improving balance is exercise-based balance rehabilitation. Despite its effectiveness, balance rehabilitation does not always result in a full recovery of balance function. In this dissertation, vibrotactile sensory augmentation (SA) and machine learning (ML) were studied as approaches for further improving balance rehabilitation outcomes. Vibrotactile SA provides a form of haptic cues to complement and/or replace sensory information from the somatosensory, visual and vestibular sensory systems. Previous studies have shown that people can reduce their body sway when vibrotactile SA is provided; however, limited controlled studies have investigated the retention of balance improvements after training with SA has ceased. The primary aim of this research was to examine the effects of supervised balance rehabilitation with vibrotactile SA. Two studies were conducted among people with unilateral vestibular disorders and healthy older adults to explore the use of vibrotactile SA for therapeutic and preventative purposes, respectively. The study among people with unilateral vestibular disorders provided six weeks of supervised in-clinic balance training. The findings indicated that training with vibrotactile SA led to additional body sway reduction for balance exercises with head movements, and the improvements were retained for up to six months. Training with vibrotactile SA did not lead to significant additional improvements in the majority of the clinical outcomes except for the Activities-specific Balance Confidence scale. The study among older adults provided semi-supervised in-home balance rehabilitation training using a novel smartphone balance trainer. After completing eight weeks of balance training, participants who trained with vibrotactile SA showed significantly greater improvements in standing-related clinical outcomes, but not in gait-related clinical outcomes, compared with those who trained without SA. In addition to investigating the effects of long-term balance training with SA, we sought to study the effects of vibrotactile display design on people’s reaction times to vibrational cues. Among the various factors tested, the vibration frequency and tactor type had relatively small effects on reaction times, while stimulus location and secondary cognitive task had relatively large effects. Factors affected young and older adults’ reaction times in a similar manner, but with different magnitudes. Lastly, we explored the potential for ML to inform balance exercise progression for future applications of unsupervised balance training. We mapped body motion data measured by wearable inertial measurement units to balance assessment ratings provided by physical therapists. By training a multi-class classifier using the leave-one-participant-out cross-validation method, we found approximately 82% agreement among trained classifier and physical therapist assessments. The findings of this dissertation suggest that vibrotactile SA can be used as a rehabilitation tool to further improve a subset of clinical outcomes resulting from supervised balance rehabilitation training. Specifically, individuals who train with a SA device may have additional confidence in performing balance activities and greater postural stability, which could decrease their fear of falling and fall risk, and subsequently increase their quality of life. This research provides preliminary support for the hypothesized mechanism that SA promotes the central nervous system to reweight sensory inputs. The preliminary outcomes of this research also provide novel insights for unsupervised balance training that leverage wearable technology and ML techniques. By providing both SA and ML-based balance assessment ratings, the smart wearable device has the potential to improve individuals’ compliance and motivation for in-home balance training.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143901/1/baotian_1.pd