Motion Analysis


Spaulding's Motion Analysis Laboratory combines laboratory and field assessments to enhance mobility.

Paolo Bonato, PhD

Spaulding's Motion Analysis Laboratory combines laboratory and field assessments to enhance mobility in individuals with mobility limiting conditions caused by age, illness, or trauma. Research topics include cerebral palsy, enhancing balance impairment, treatment of drop foot, gait retraining for victims of stroke and brain injury, restoration of gait to amputees, and biomechanical analysis of Tae Kwan Do.

Assessing Usability of the ARMEO Robotic Device for Upper Extremity Training of Individuals with Neurological Impairments
PI: Paolo Bonato
The ARMEO is an arm robotic exoskeleton device that combines gravity support with virtual reality exercises for use in individuals with neurological conditions. Preliminary clinical tests showed positive results including increased range of motion of the affected limb, increased enjoyment, motivation and attention compared to traditional rehabilitation exercises. Spaulding Rehabilitation Hospital has recently received the ARMEO device as a loan at no cost. The technology is novel and has only been studied on a small group of individuals. Therefore the aims of this usability study are to test the device and its applicability for training of the arm of individuals with neurological upper extremity (UE) impairments. Specifically this study will evaluate 1) the movement control and support of the robotic arm, and 2) the appropriateness of the virtual reality games for this population.

Robotic Assessment of Lower Extremity Motor Learning
PI: Paolo Bonato
The Lokomat is a gait orthosis platform developed by Hocoma AG of Switzerland. The Lokomat introduces small force perturbations during baseline Lokomat walking that induces trajectory errors to which the subjects must then adapt. This study's objective is to apply a motor learning paradigm commonly used in upper-arm motor learning experiments to lower-extremity motor learning. The implementation of this paradigm may allow for a novel method of robotic assessment of motor learning.

Effect of Tai Chi on Musculoskeletal Loading and Balance Control of Osteopenic Women
PI: Paolo Bonato
Women untreated for low bone density are at a high risk for further bone loss and its associated complications, including a higher risk of bone fractures. Current guidelines for treating these osteopenic women include the recommendation of regular exercise. However, there is currently no consensus regarding the optimal types and regimens of exercise for treating low bone mineral density, or for addressing other risk factors associated with osteopenia (e.g. poor balance, decreased muscle strength, diminished agility). Tai Chi, a meditative/mind-body exercise that integrates a variety of modalities (e.g. weight bearing exercise, balance training, imagery) shows strong potential as an effective, sustainable, safe and practical intervention for women with low bone density. This study will collect preliminary data using biomechanical analyses and clinical assessments of gait, quiet/tandem standing, and chair rise in two groups of post-menopausal osteopenic women – one group undertaking community based Tai Chi training as an adjunct to standard of care for osteopenia and the other a control group following standard of care for osteopenia alone.

An In-Shoe Device to Monitor Toe-Walking in Children with Cerebral Palsy
PI: Paolo Bonato
This project seeks to demonstrate the efficacy of an unobtrusive, wearable, in-shoe gait monitoring device (ActiveGait, Simbex) to capture accurate foot center-of-pressure and ankle mechanics data compared to laboratory-based motion capture data. This study will focus on children with cerebral palsy (CP) who exhibit a toe-walking gait pattern. We plan to classify motor tasks (level walking, ramp and stair ambulation) on the basis of in-shoe data for a CP population using data mining/clustering algorithms. We also plan to explore the development of a Toe Walking Severity (TWS) index from available biomechanical and ActiveGait data for different ambulatory conditions. The device and tools we will develop will help in the long term monitoring of children with CP who undergo rehabilitative interventions. This work is being done in collaboration with Simbex LCC, Lebanon, NH.

Assessing the use of the Nintendo Wii in the Rehabilitation of Stroke Patients
PI: Yong-Tae Lee
This study aims to assess the effects of the use of the Nintendo Wii on the rehabilitation of stroke victims. We seek to explore the utility of the Wii in a rehabilitation context, where we suspect that its use may help increase endurance, compliance and functional recovery in patients who have suffered a stroke. Current studies have shown that virtual reality environments can help facilitate motor recovery in patients with functional deficits improving on range of motion, the ability to remain standing, and more. It has also been effective in distracting some patients from pain during exercise.

Pelvic Obliquity Rehabilitation in Stroke Patients Using Robotically-Generated Force Fields
PI: Paolo Bonato
Many stroke survivors demonstrate a characteristic posture during quiet standing and those who walk demonstrate abnormal gait patterns associated with gait instability. These abnormalities need to be corrected via gait retraining. This study tests the usability and effectiveness of the Robotic Gait Rehabilitation Trainer in both healthy patients with no gait impairment and those with stroke and gait abnormalities. This robotic device applies force fields to a patient's pelvic area to help train stroke patients to correct abnormal gait patterns involving exaggerated movements of the pelvis. Our study will evaluate both the effectiveness and user-functionality of the RGRT.

Motor Unit Behavior In Amyotrophic Lateral Sclerosis (ALS)
PI: Paolo Bonato
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of the upper and lower motor neurons. Routine clinical neurophysiological studies provide a measure of the presence of motor neuron disease, but lack specificity. Disease quantification is also limited. This project's objective is to characterize the motor unit discharge rate (MUDR) in patients with ALS, those with strictly upper or lower motor neuron disorders, as well as normal control subjects. We will follow changes in the MUDR over a period of six months and correlate these MUDR measurements and changes with compound motor action potential (CMAP) amplitude, muscle force, ALS FRS-R and spasticity. We believe that those with pure lower motor neuron dysfunction will have decreased CMAP and increased MUDR while those with pure upper motor neuron dysfunction will have normal CMAP amplitude and decreased MUDR. Those with ALS, we hypothesize will have a decreased CMAP amplitude and variable MUDR.

Assessment of a Novel Gaming System for Children with Upper-Extremity Burn Contractures.
PI: Schneider
Contractures or the inability to perform the full range of motion of a joint, are common after a burn injury. As many as one-third of burn patients have at least one large joint contracture at the time of hospital discharge. Burn clinicians are compelled to find novel ways to treat contractures. Our team has recently turned its attention to the use of interactive gaming to implement rehabilitation interventions. The ARMEO system, in particular, allows clinicians to control a patient's range of movement and to encourage subjects to increase the range over time. We hypothesize that a new gaming system aimed specifically at children undergoing burn rehabilitation will be a useful rehabilitation tool that will enable clinicians to achieve clinical goals of facilitating the performance of a given set of movements (i.e. kids will span a given range of movement according to the way we set up the ARMEO system).

Structural Integration for Chronic Lower Back Pain
PI: Paolo Bonato
Chronic low back pain is among the most burdensome health problems in both prevalence and cost of care. Up to one-third of acute low back pain cases become chronic and lead to disability. A large fraction of chronic cases are absent findings of well-understood causes. Structural integration (SI) is a method of manual therapy developed by Ida Rolf which has been developed and propagated outside of orthodox medical practice. SI purports to improve the performance of the entire biomechanical system rather than focus on local areas of pain or dysfunction as physical therapy, osteopathic manipulation and chiropractics ordinarily do. This study seeks to examine 10 patients in a pilot trial of a standardized course of SI plus usual care versus usual care alone. Data will also be collected on factors hypothesized to contribute to the therapeutic effect: a) cognitive-behavioral factors and psychological morbidities known to be associated with low back pain  and b) deficits in biomechanical performance: postural sway in standing and coordination of gait.  Qualitative data on the illness and therapeutic experience of the research subjects will also be collected and subjected to an interpretive analysis.

Robotic Gait Training in Children with Cerebral Palsy
PI: Paolo Bonato
In children with CP, high lower limb agonist-antagonist muscle co-activations, increased tone, tightness of Achilles tendon and knee and hip musculature are reported causes of abnormal gait and high energy expenditure during ambulation. Techniques for correcting such gait problems include Body Weight Supported Treadmill Training (BWSTT).  In a recent study, patients walked more symmetrically, less spastically, and more efficiently on the treadmill with body weight support than in normal circumstances. Recent development of a motorized locomotor training device, the Lokomat (Hocoma AG, Switzerland), may improve delivery of BWSTT. The Lokomat is a computer-controlled exoskeleton that is secured to a person’s lower limbs while he/she is supported over a motorized treadmill using a counterweight unloading system. The motorized exoskeleton replaces the manual assistance provided by therapists.  The proposed study is a pilot study to investigate the suitability of the device for training children with CP, and the development of protocols that will allow clinicians to achieve in children with CP the encouraging results already attained in other adult patient populations.

The Effect of Transcranial Direct Current Stimulation Combined with Functional Task Training on Motor Recovery in Traumatic Brain Injury and Stroke Survivors
PI: Paolo Bonato
Various approaches have been used by researchers to facilitate motor recovery in patients undergoing rehabilitation. Among others, transcranial direct current stimulation (tDCS) is of particular interest because of its ability to facilitate motor recovery. It is our hypothesis that coupling transcranial direct current stimulation with functional task training will enhance the effect on motor recovery in traumatic brain injury survivors. The purpose of this study is to demonstrate that tDCS combined with upper-extremity functional task training in a virtual environment, is more effective than functional task training in the virtual environment with sham tDCS.

The Effect of Repetitive Upper Arm Training in a Virtual Environment on Upper Extremity Motor Recovery in Chronic-Stroke Survivors.
PI: Paolo Bonato
The ability to reach and grasp is a necessary component of many daily-life functional tasks. When patients are impaired in reach and grasp, they compensate by using the trunk to transport the hand.  We intend to test the use of a virtual game that includes a glove, grip and sensors, with stroke patients that is intended to rehabilitation the arms to address this problem.We will test the efficacy of both a fixed grip and sensor as well as a flexible one to see which performs the best in rehabilitation.

PD Motor Fluctuation Study
PI: Paolo Bonato
Parkinson’s disease is the most common neuro-degenerative disease, affecting about 3% of the population over the age of 65 years. The main goal of this project is to use our wireless wearable sensor system (consisting of accelerometers and gyroscopes) to monitor motor fluctuations in patients with Parkinson’s disease. The focus is on patients with late-stage PD with levodopa-related movement disorders and motor fluctuations characterized by ON and OFF periods. Using data mining techniques we will analyze data collected using wearable sensors and develop algorithms to predict clinical scores. In addition to successfully predicting clinical scores for the purpose of assessment, data mining has the potential to increase our understanding of these disorders.

Monitoring Motor Patterns of Epileptic Seizures Using Wearable Sensor Technologies
This study will evaluate the use of miniature wearable movement sensors attached to the body to monitor physical and physiological signals related to motor movements that accompany seizures of epilepsy patients. We will study patients who are likely to have seizures as part of a clinically-indicated hospitalization. In support of our goal of developing a wearable system allowing physicians the long-term monitoring of patients with epileptic seizures, we will 1) develop algorithms for the identification of patterns of movement and physiological responses associated with seizure events; and 2) assess the likelihood of false positives when data related to activities of daily living are fed to the algorithms developed to identify the occurrence of seizures.

Improving Recovery after Stroke via Electrical Stimulation of Proprioceptors
PI: Paolo Bonato
Until recently, improvements in motor function after stroke were believed to be greatest during the first 6 months following stroke, with little to no progress after 6 to 12 months. Recent research has shown that gains in motor function can occur with intensive motor-learning-based rehabilitation even many years post stroke [6-8]. This study aims to assess the effectiveness of robotic and virtual reality training in neurorehabilitation. The project will require the development of an easy-to-use, compact stimulation system and will determine an optimal level of stimulation to maximize the benefits of the stimulation technique. To achieve clinical assessment of the proposed method we will rely on the combination of robotic-assisted rehabilitation and SR.

Combining Galvanic Vestibular Stimulation (GVS) and Motor Training in Traumatic Brain Injury Survivors with Attentional Deficits
PI: Paolo Bonato
Traumatic Brain Injury (TBI) is world-wide a major public health problem. We will study the effect of combining GVS and motor training in a small cohort of TBI survivors. Our patients will receive GVS while undertaking motor training delivered via a robotic system with virtual reality modules. Subjects will be randomly assigned to one of two treatment conditions: active GVS and sham GVS (control). The active GVS will be the optimal stimulation settings determined from the first part of the study. We will assess functional outcomes from the treatment via cognitive testing. We plan to explore the use of GVS in combination with motor training delivered via robot-assisted and virtual reality-based physical therapy, in particular, the ARMEO robotic system and a gaming environment (on a computer screen) designed to achieve functional movements, i.e. the subject has to perform tasks such as reaching for objects as part of the game. 

Randomized ActiveStep® Comparative Effectiveness Trial (RACE-T)
PI: Paolo Bonato
The overall objective of the proposed study is to assess the outcomes of balance training interventions using a device named the ActiveStep® training system and compare them with the outcomes of traditional balance training techniques.  The ActiveStep® device is a treadmill-based system designed to introduce random perturbations while patients ambulate on the treadmill by moving the belt of the treadmill in an irregular way.  It follows that subjects experience a perturbation similar to a trip or slip as often experienced before a fall.  The hypothesis underlying the design of the system is that patients need to learn how to respond to realistic perturbations during walking in order to effectively reduce fall rate.


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