Rahul Soangra

Effects of hemodialysis therapy on sit-to-walk characteristics in end stage renal disease patients.

Patients with end stage renal diseases (ESRD) undergoing hemodialysis (HD) have high morbidity and mortality due to multiple causes; one of which is dramatically higher fall rates than the general population. In spite of the multiple efforts aiming to decrease the high mortality and improve quality of life in ESRD patients, limited success has been achieved. If adequate interventions for fall prevention are to be achieved, the functional and mobility mechanisms consistent with falls in this population must be understood. Human movements such as sit-to-walk (STW) tasks are clinically significant, and analysis of these movements provides a meaningful evaluation of postural and locomotor performance in elderly patients with functional limitations indicative of fall risks. In order to assess the effects of HD therapy on fall risks, 22 sessions of both pre- and post-HD measurements were obtained in six ESRD patients utilizing customized inertial measurement units (IMU). IMU signals were denoised using ensemble empirical mode decomposition and Savistky-Golay filtering methods to detect relevant events for identification of STW phases. The results indicated that patients were slower to get out of the chair (as measured by trunk flexion angular accelerations, time to peak trunk flexion, and overall STW completion time) following the dialysis therapy session. STW is a frequent movement in activities of daily living, and HD therapy may influence the postural and locomotor control of these movements. The analysis of STW movement may assist in not only assessing a patient’s physical status, but in identifying HD-related fall risk as well. This preliminary study presents a non-invasive method of kinematic measurement for early detection of increased fall risk in ESRD patients using portable inertial sensors for out-patient monitoring. This can be helpful in understanding the pathogenesis better, and improve awareness in health care providers in targeting interventions to identify individuals at risk for fall.

Investigation into the Functional Mobility Difference between Obese and Non-Obese Elderly

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 and obese elderly. Stopwatch and custom-made inertial measurement units were used to obtain the temporal and kinematic parameters. The results showed that there is no significant difference in overall time to complete the “timed up & go” task, but significant difference in anterior posterior acceleration, time to reach the peak extension angular velocity from initiation and double support time between lean and obese groups of participants. Therefore, we concluded that older obese adults have some functional mobility impairments compared with their lean counterparts but the completion time of the “timed up & go” test may not be able to differentiate these individuals. Our results also suggested that obese elderly might have more muscular impairments than their healthy weight counterparts, which can result in higher fall risks. Future studies are warranted to investigate the mechanisms of increased fall risks among obese elderly.

Effects of Anti-Fatigue Flooring on Gait Parameters

Falls among industrial workers are the leading cause of work related injuries. Nowadays, many industries are opting for anti-fatigue cushioned flooring to reduce fall-related socio-economic cost. The goal of this study is to test SATECHs anti-fatigue flooring for stable gait. A pilot test with five healthy subjects (25–35 years old) has been conducted with six motion capture cameras and two force platforms embedded in a walkway to obtain kinematics and kinetics of whole body gait on two different floors. In conditions where the same floor material was used on the whole walkway, the anti-fatigue floor had smaller values of step length (p<0.01) associated with walking and lower values of required coefficient of friction (RCOF) (p<0.05). Toe clearance, heel contact velocity, whole body center of mass (COM) velocity, single foot stance, and double foot stance did not show significant differences between conditions. The results of this study suggest that subjects were to follow a more stable gait on the SATECH anti-fatigue flooring.

Recurrence Quantitative Analysis of Postural Sway using Force Plate and Smartphone

Although modern medicine and new medical technologies offer enormous potential to improve diagnosis and treatment of many diseases, mortalities from fall accidents are steadily on the rise for the elderly. Since postural stability characteristics are considered to be important in maintaining functional independence free of falls and healthy life style especially for the growing elderly population, there is an imminent need in inexpensive and portable device that can assess balance. While inertial sensors embedded in smartphone are seen as an alternative to force plate (ground truth) to unobtrusively assess postural stability in home environments, no study has yet reported the non-linear physiological information captured by smartphone affixed at pelvic region. By using recurrence quantitative analysis (RQA), this study investigates non-linear dynamical features of postural sway measured from force plate and smartphone. The resultant position vector of postural sway from the two systems was highly coherent and was used for non-linear analysis. Even though most of RQA measures collected from the projected postural sway using the smartphone were significantly different than measures collected using the force plate, deterministic characteristics of postural sway were not found significantly different. This study opens new prospects of easy clinical testing using postural variables that may be relevant for assessing fall risks at home and patient environment in future.

An approach for identifying gait events using wavelet denoising technique and single wireless IMU

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 comparing the results of video-based motion capture system and force plates as conventional standards. This portable gait-monitoring system allows for versatile application beyond gait laboratory.

Inertial sensor-based variables are indicators of frailty and adverse post-operative outcomes in cardiovascular disease patients

Cardiovascular disease (CVD) patients with intrinsic cardiac cause for falling have been found to be frail and submissive to morbidity and mortality as post-operative outcomes. In these older CVD patients, gait speed is conjectured by the Society of Thoracic Surgeons (STS) as an independent predictor of post-operative morbidity and mortality. However, this guideline by STS has not been studied adequately with a large sample size; rather it is based largely on expert opinions of cardiac surgeons and researchers. Although one’s gait speed is not completely associated with one’s risk of falls, gait speed is a quick robust measure to classify frail/non-frail CVD patients and undoubtedly frail individuals are more prone to falls. Thus, this study examines the effects of inertial sensor-based quick movement variability characteristics in identifying CVD patients likely to have an adverse post-operative outcome. This study establishes a relationship with gait and postural predictor variables with patient’s post-operative adverse outcomes. Accordingly, inertial sensors embedded inside smartphones are indispensable for the assessment of elderly patients in clinical environments and may be necessary for quick objective assessment. Sixteen elderly CVD patients (Age 76.1 ± 3.6 years) who were scheduled for cardiac surgery the next day were recruited for this study. Based on STS recommendation guidelines, eight of the CVD patients were classified as frail (prone to adverse outcomes with gait speed ≤ 0.833 m/s) and the other eight patients as non-frail (gait speed > 0.833 m/s). Smartphone-derived walking velocity was found to be significantly lower in frail patients than that in non-frail patients (p < 0.01). Mean Center of Pressure (COP) radius (p < 0.01), COP Area (p < 0.01), COP path length (p < 0.05) and mean COP velocity (p < 0.05) were found to be significantly higher in frail patients than that in the non-frail patient group. Nonlinear variability measures such as sample entropy were significantly lower in frail participants in anterior-posterior (p < 0.01) and resultant sway direction (p < 0.01) than in the non-frail group. This study identified numerous postural and movement variability parameters that offer insights into predictive inertial sensor-based variables and post-operative adverse outcomes among CVD patients. In future, smartphone-based clinical measurement systems could serve as a clinical decision support system for assessing patients quickly in the perioperative period.

Fall Risk Prediction Using Wearable Wireless Sensors

Falls are the primary cause of accidental death and injury-related visits to emergency departments in the elderly population. In 2010 alone, 2.3 million nonfatal fall injuries were treated in emergency departments, and approximately 21,700 of those culminated in death, with direct medical costs totaling

Dynamical Properties of Postural Control in Obese Community-Dwelling Older Adults †

30 billion.1 Accordingly, fall prevention requires techniques for accurate assessment of fall risk of individuals, whereas traditional diagnostics entail retrospective observation and rudimentary subjective inspection. Thus, the greatest need for elderly individuals—and health care in general—is arguably predictive techniques and technologies to distinguish elderly individuals at risk of falls. Postural stability measures have been used to determine the risk of fall for a given individual to provide optimal prevention, diagnosis, and treatment.2, 3 Assessments typically occur periodically, performed by physicians who rely on patient self-reports and visual inspection in their diagnosis, measures that lack objectivity and sensitivity, and consequently often culminate in data inaccuracies. Advanced assessments likely include a referral to a laboratory force platform that may be travel-dependent and economically unfeasible. Accordingly, we investigated the potential of inexpensive wearable wireless sensors as an alternative to the force platform.4 One hundred community-dwelling elderly volunteers (56–90 years old, mean age 74:3 ̇ 7:6 years) participated in this study. Subjects’ histories of falls were recorded for the previous 2 years, with an emphasis on frequency and characteristics of falls. Subjects with at least one fall in the prior year were classified as fallers and the others as nonfallers. The study was conducted in four different community centers using a force plate and an inertial measurement unit (IMU). This study was approved by the Virginia Tech Institutional Review Board and was conducted in collaboration with Northern Virginia Fall Prevention Figure 1. Placing the fall risk monitor on an elderly person during the motion-capture experiment.

Motor Subtypes of Parkinson’s Disease Can Be Identified by Frequency Component of Postural Stability

Postural control is a key aspect in preventing falls. The aim of this study was to determine if obesity affected balance in community-dwelling older adults and serve as an indicator of fall risk. The participants were randomly assigned to receive a comprehensive geriatric assessment followed by a longitudinal assessment of their fall history. The standing postural balance was measured for 98 participants with a Body Mass Index (BMI) ranging from 18 to 63 kg/m2, using a force plate and an inertial measurement unit affixed at the sternum. Participants’ fall history was recorded over 2 years and participants with at least one fall in the prior year were classified as fallers. The results suggest that body weight/BMI is an additional risk factor for falling in elderly persons and may be an important marker for fall risk. The linear variables of postural analysis suggest that the obese fallers have significantly higher sway area and sway ranges, along with higher root mean square and standard deviation of time series. Additionally, it was found that obese fallers have lower complexity of anterior-posterior center of pressure time series. Future studies should examine more closely the combined effect of aging and obesity on dynamic balance.

A Case Report of Shoulder Fatigue Imbalance in Wheelchair Rugby: Implications to Pain and Injury

Parkinson’s disease (PD) can be divided into two subtypes based on clinical features—namely tremor dominant (TD) and postural instability and gait difficulty (PIGD). This categorization is important at the early stage of PD, since identifying the subtypes can help to predict the clinical progression of the disease. Accordingly, correctly diagnosing subtypes is critical in initiating appropriate early interventions and tracking the progression of the disease. However, as the disease progresses, it becomes increasingly difficult to further distinguish those attributes that are relevant to the subtypes. In this study, we investigated whether a method using the standing center of pressure (COP) time series data can separate two subtypes of PD by looking at the frequency component of COP (i.e., COP position and speed). Thirty-six participants diagnosed with PD were evaluated, with their bare feet on the force platform, and were instructed to stand upright with their arms by their sides for 20 s (with their eyes open and closed), which is consistent with the traditional COP measures. Fast Fourier transform (FFT) and wavelet transform (WT) were performed to distinguish between the motor subtypes using the COP measures. The TD group exhibited larger amplitudes at the frequency range of 3–7 Hz when compared to the PIGD group. Both the FFT and WT methods were able to differentiate the subtypes. COP time series information can be used to differentiate between the two motor subtypes of PD, using the frequency component of postural stability.