Movement and Mind-Body Therapies Commons^™

A Single-Center, Assessor-Blinded, Randomized Controlled Clinical Trial To Test The Safety And Efficacy Of A Novel Brain-Computer Interface Controlled Functional Electrical Stimulation (Bci-Fes) Intervention For Gait Rehabilitation In The Chronic Stroke Population, Piyashi Biswas, Lucy Dodakian, Po T. Wang, Christopher A. Johnson, Jill See, Vicky Chan, Cathy Chou, Wendy Lazouras, Alison L. Mckenzie, David J. Reinkensmeyer, Danh V. Nguyen, Steven C. Cramer, An H. Do, Zoran Nenadic

Physical Therapy Faculty Articles and Research

Background

In the United States, there are over seven million stroke survivors, with many facing gait impairments due to foot drop. This restricts their community ambulation and hinders functional independence, leading to several long-term health complications. Despite the best available physical therapy, gait function is incompletely recovered, and this occurs mainly during the acute phase post-stroke. Therapeutic options are limited currently. Novel therapies based on neurobiological principles have the potential to lead to long-term functional improvements. The Brain-Computer Interface (BCI) controlled Functional Electrical Stimulation (FES) system is one such strategy. It is based on Hebbian principles and has shown promise …

An End-To-End Cnn With Attentional Mechanism Applied To Raw Eeg In A Bci Classification Task, Elnaz Lashgari, Jordan Ott, Akima Connelly, Pierre Baldi, Uri Maoz

Psychology Faculty Articles and Research

Objective. Motor-imagery (MI) classification base on electroencephalography (EEG) has been long studied in neuroscience and more recently widely used in healthcare applications such as mobile assistive robots and neurorehabilitation. In particular, EEG-based motor-imagery classification methods that rely on convolutional neural networks (CNNs) have achieved relatively high classification accuracy. However, naively training CNNs to classify raw EEG data from all channels, especially for high-density EEG, is computationally demanding and requires huge training sets. It often also introduces many irrelevant input features, making it difficult for the CNN to extract the informative ones. This problem is compounded by a dearth of training …

Revealing The Optimal Thresholds For Movement Performance: A Systematic Review And Meta-Analysis To Benchmark Pathological Walking Behaviour, Deepak K. Ravi, Michelle Gwerder, Niklas König Ignasiak, Christian R. Baumann, Mechtild Uhl, Jaap H. Dieën, William R. Taylor, Navrag B. Singh

Physical Therapy Faculty Articles and Research

In order to address whether increased levels of movement output variability indicate pathological performance, we systematically reviewed and synthesized meta-analysis data on healthy and pathological motor behavior. After screening up to 24’000 reports from four databases, 85 studies were included containing 2409 patients and 2523 healthy asymptomatic controls. The optimal thresholds of variability with uncertainty boundaries (in % Coefficient of Variation ± Standard Error) were estimated in 7 parameters: stride time (2.34 ± 0.21), stride length (2.99 ± 0.37), step length (3.34 ± 0.84), swing time (2.94 ± 0.60), step time (3.35 ± 0.23), step width (15.87 ± 1.86), …

Wavelet-Based Analysis Of Physical Activity And Sleep Movement Data From Wearable Sensors Among Obese Adults, Rahul Soangra, Vennila Krishnan

Physical Therapy Faculty Articles and Research

Decreased physical activity in obese individuals is associated with a prevalence of cardiovascular and metabolic disorders. Physicians usually recommend that obese individuals change their lifestyle, specifically changes in diet, exercise, and other physical activities for obesity management. Therefore, understanding physical activity and sleep behavior is an essential aspect of obesity management. With innovations in mobile and electronic health care technologies, wearable inertial sensors have been used extensively over the past decade for monitoring human activities. Despite significant progress with the wearable inertial sensing technology, there is a knowledge gap among researchers regarding how to analyze longitudinal multi-day inertial sensor data …

Efficacy Of Electromyography And The Dead Bug Exercise, Taylor M. Scavo, Rachel C. Cooklin, Erika N. Faria, Madeline L. Johnson, Eric Sternlicht

Student Scholar Symposium Abstracts and Posters

The Dead Bug exercise is performed in physical therapy clinics to restore lumbar spine stability and core strength in patients with lower back pain (LBP). The aim of this study was to evaluate the efficacy of using electromyography (EMG) feedback to enhance proper mechanics during the Dead Bug exercise. Sixteen healthy, college age students volunteered as subjects for the study. Subjects performed the Dead Bug (Fig. 1a.) with and without visual EMG cues and were given instructions on how to execute the exercise. Data was recorded using a BTS FREEEMG Analyzer and signal processed and data analyzed using the BTS …

Dual-Task Does Not Increase Slip And Fall Risk In Healthy Young And Older Adults During Walking, Rahul Soangra, Thurmon Lockhart

Physical Therapy Faculty Articles and Research

Dual-task tests can identify gait characteristics peculiar to fallers and nonfallers. Understanding the relationship between gait performance and dual-task related cognitive-motor interference is important for fall prevention. Dual-task adapted changes in gait instability/variability can adversely affect fall risks. Although implicated, it is unclear if healthy participants’ fall risks aremodified by dual-task walking conditions. Seven healthy young and seven healthy older adults were randomly assigned to normal walking and dual-task walking sessions with a slip perturbation. In the dual-task session, the participants walked and simultaneously counted backwards from a randomly provided number. The results indicate that the gait changes in dual-task …

1st Place Research Paper: The Effectiveness Of Yoga Therapy On An Adult, Post-Stroke Population: A Systematic Review, Baylor E. Hogan

Kevin and Tam Ross Undergraduate Research Prize

Objectives: The objectives of this paper are to (1) give a brief overview of stroke pathophysiology (2) outline yoga as a therapeutic strategy (3) present the current research on yoga rehabilitation for stroke (4) discuss the efficacy of yoga for chronic stroke.

Methods: Relevant terms were searched in PubMed, Web of Science, Academic OneFile, ScienceDirect, and Google Scholar electronic databases. Studies were excluded if they contained pediatric stroke, non-stroke neurological diseases, or subjects with comorbidities. Statistically significant data was extracted for the primary measures of nine trials.

Results: Four studies measured statistically significant outcomes (p<0.05). These included improvements in balance, independence, endurance, trait anxiety, fear of falling, self-efficacy, pain, strength, range of motion (ROM), activity, participation, and quality of life (QoL). Discussion: Lack of statistical significance in post-stroke depression (PSD) measures may be due to inadequate intervention length or a psychosocial cause of depression. Improvements in balance, flexibility, and strength from yoga participation permitted progress in disability and functionality. Finally, overall health-related quality of life (HRQL) is affected by the severity of mental disorders and physical disability. Yoga can have a positive effect in both domains and therefore, may improve HRQL.

Conclusion: …

1st Place Contest Entry: The Effectiveness Of Yoga Therapy On An Adult, Post-Stroke Population: A Systematic Review, Baylor E. Hogan

Kevin and Tam Ross Undergraduate Research Prize

This is Baylor Hogan's submission for the 2016 Kevin and Tam Ross Undergraduate Research Prize, which won first place. She wrote about the effects of yoga therapy on the physical and mental wellbeing of stroke patients. You can read the final essay that came out of her research here.

Baylor is a senior at Chapman University, majoring in Kinesiology. Her faculty mentor is Dr. Elizabeth DeBaets.

Choice Of Human–Computer Interaction Mode In Stroke Rehabilitation, Hossein Mousavi Hondori, Maryam Khademi, Lucy Dodakian, Alison Mackenzie, Cristina V. Lopes, Steven C. Cramer

Physical Therapy Faculty Articles and Research

Background and Objective. Advances in technology are providing new forms of human–computer interaction. The current study examined one form of human–computer interaction, augmented reality (AR), whereby subjects train in the real-world workspace with virtual objects projected by the computer. Motor performances were compared with those obtained while subjects used a traditional human–computer interaction, that is, a personal computer (PC) with a mouse. Methods. Patients used goal-directed arm movements to play AR and PC versions of the Fruit Ninja video game. The 2 versions required the same arm movements to control the game but had different cognitive demands. With …

Fall Risk Prediction Using Wearable Wireless Sensors, Thurmon Lockhart, Chris Frame, Rahul Soangra, John Lach

Physical Therapy Faculty Articles and Research

Wearable wireless sensors and nonlinear dynamics identify postural characteristics relevant to balance control and dynamic stability, revealing predictive risk of falls among older adults.

Potential For Using Smartphone Accelerometers In Non-Laboratory Environments, Rahul Soangra, Thurmon Lockhart, Christopher W. Frames, Jian Zhang, Seong Hyun Moon, Jongsoon Park

Physical Therapy Faculty Articles and Research

In recent years, there has been rising interest in using accelerometers as an alternative instrument to measure the center of pressure. Accelerometers are inexpensive, small, sensitive, and can be readily used in non-laboratory environments. In addition to this, smartphones with built-in accelerometers add to their capability with real-time processing of data from sensors. Clinicians and researchers are currently in disagreement from whether these measurements provide the same physiological information about the participant’s balance. In this study, twelve participants were asked to wear smartphone on their right ASIS using a belt clip and stand still on the forceplate. The data was …

Applying Principles Of Motor Learning And Control To Upper Extremity Rehabilitation, Lisa M. Muratori, Eric M. Lamberg, Lori Quinn, Susan V. Duff

Physical Therapy Faculty Articles and Research

The purpose of this article is to provide a brief review of the principles of motor control and learning. Different models of motor control from historical to contemporary are presented with emphasis on the Systems model. Concepts of motor learning including skill acquisition, measurement of learning, and methods to promote skill acquisition by examining the many facets of practice scheduling and use of feedback are provided. A fictional client case is introduced and threaded throughout the article to facilitate understanding of these concepts and how they can be applied to clinical practice.

Investigation Into The Functional Mobility Difference Between Obese And Non-Obese Elderly, Xuefang Wu, Han T. Yeoh, Rahul Soangra, Thurmon Lockhart

Physical Therapy Faculty Articles and Research

Obese aging population is increasing in the United States, and obese elderly experience fall twice as frequent as their lean counterparts. However, the mechanisms of older obese adults fall are still not clear. It is not known whether the obese elderly has more functional mobility impairments than their lean counterparts, and consequently have increased risks of falls. It was hypothesized that obese elderly have more functional mobility impairments compared with their healthy weight counterparts. Six lean and six obese community-dwelling elderly participated in the study. “Timed up & go” test was used to quantify the functional mobility for both lean …

An Approach For Identifying Gait Events Using Wavelet Denoising Technique And Single Wireless Imu, Rahul Soangra, Thurmon Lockhart, Nathalie Van De Berge

Physical Therapy Faculty Articles and Research

A new approach is proposed to identify gait events in non-laboratory environments with a single inertial measurement unit (IMU) embedded inside shoe. The aim of our work is to develop a useful clinical tool for monitoring individuals walking disability and detect specific pathological gait patterns. Temporal parameters of gait are determined by classification of accelerations and angular velocities. Wavelets denoising of IMU signals allows for an important amount of information that is exploited in different manners for event identification. It was found that wavelet denoising enhanced specific turning points which could effectively identify gait events. The method is verified by …

Portable, Non-Invasive Fall Risk Assessment In End Stage Renal Disease Patients On Hemodialysis, Thurmon Lockhart, Adam T. Barth, Xiaoyue Zhang, Rahul Soangra, Emaad Abdel-Rahman, John Lach

Physical Therapy Faculty Articles and Research

Patients with end stage renal diseases (ESRD) on hemodialysis (HD) have high morbidity and mortality due to multiple causes, one of which is dramatically higher fall rates than the general population. The mobility mechanisms that contribute to falls in this population must be understood if adequate interventions for fall prevention are to be achieved. This study utilizes emerging noninvasive, portable gait, posture, strength, and stability assessment technologies to extract various mobility parameters that research has shown to be predictive of fall risk in the general population. As part of an ongoing human subjects study, mobility measures such as postural and …

The Impact Of Left Hemisphere Stroke On Force Control With Familiar And Novel Objects: Neuroanatomic Substrates And Relationship To Apraxia, Amanda M. Dawson, Laura J. Buxbaum, Susan V. Duff

Physical Therapy Faculty Articles and Research

Fingertip force scaling for lifting objects frequently occurs in anticipation of finger contact. An ongoing question concerns the types of memories that are used to inform predictive control. Object-specific information such as weight may be stored and retrieved when previously encountered objects are lifted again. Alternatively, visual size and shape cues may provide estimates of object density each time objects are encountered. We reasoned that differences in performance with familiar versus novel objects would provide support for the former possibility. Anticipatory force production with both familiar and novel objects was assessed in six left hemisphere stroke patients, two of whom …