Clinical balance assessments often rely on functional tasks as a proxy for balance (e.g., Timed Up and Go). In contrast, analyses of balance in research settings incorporate quantitative biomechanical measurements (e.g., whole-body angular momentum, H) using motion capture techniques. Fully instrumenting patients in the clinic is not feasible, and thus it is desirable to estimate biomechanical quantities related to balance from measurements taken from a subset of the body segments. Machine learning algorithms are well-suited for this type of low- to high-dimensional mapping. Thus, our goal was to develop and test an artificial neural network that to predict segment contributions to whole-body angular momentum from linear acceleration and angular velocity signals (i.e., those typically available to wearable inertial measurement units, IMUs) taken from a sparse set of body segments. Optical motion capture data were collected from five able-bodied individuals and five individuals with Parkinson's disease (PD) walking on a non-steady-state locomotor circuit comprising stairs, ramps and changes of direction. Motion data were used to calculate angular momentum (i.e., “gold standard” output data) and body-segment linear acceleration and angular velocity data from local reference frames at the wrists, ankles and neck (i.e., network input). A dynamic nonlinear autoregressive neural network was trained using the able-bodied data (pooled across subjects). The neural network was tested on data from individuals with PD with noise added to simulate real-world IMU data. Correlation coefficients of the predicted segment contributions to whole-body angular momentum with the gold standard data were 0.989 for able-bodied individuals and 0.987 for individuals with PD. Mean RMS errors were between 2 and 7% peak signal magnitude for all body segments during completion of the locomotor circuits. Our results suggest that estimating segment contributions to angular momentum from mechanical signals (linear acceleration, angular velocity) from a sparse set of body segments is a feasible method for assessing coordination of balance—even using a network trained on able-bodied data to assess individuals with neurological disease. These targeted estimates of segmental momenta could potentially be delivered to clinicians using a sparse sensor set (and likely in real-time) in order to enhance balance rehabilitation of people with PD.

BACKGROUND: Parkinson disease (PD) is a progressive neurological disease resulting in motor impairments, postural instability, and gait alterations which may result in self-care limitations and loss of mobility reducing quality of life. OBJECTIVE: This study’s purpose was to determine the impact of a community-based boxing program on gait parameters, dual task and backwards walking in individuals with PD. METHODS: This study included 26 community dwelling individuals with PD who participated in 12-week boxing classes (1 hour, 2 times a week). The focus was on upper/lower extremity exercises using punching bags, agility drills, and strengthening activities. Pre/post testing was performed for dual task and gait parameters and was analyzed using t-tests. RESULTS: Analysis of the scores indicated participants performed significantly better at post-test compared to pre-test on self-selected walking velocity (P = 0.041), cadence (P = 0.021); backwards walking velocity (P = 0.003), step length (P = 0.022); dual task walking velocity (P = 0.044), step length (P = 0.023), and gait variability index (P = 0.008). No significant differences for fast walking. CONCLUSIONS: Multi-modal boxing produced improvements in gait velocity, dual task velocity, step length, and gait variability, as well as backwards walking velocity and step length. These improvements may impact independence with functional mobility and may improve safety but require further studies.

: In college and graduate programs across the United States, educators have become aware that the psychological well-being of the current generation of students (often referred to as “Millennials”) needs to be an important area of focus. In 2007, 50.7% of American college students met the clinical criteria for a depressive or anxiety disorder. In the 2010 American College Health Survey, 48% of college and university respondents felt overwhelming anxiety at least once in the preceding year. These data make it clear that there is a need for effective interventions to help students reduce the emotional distress they experience. This pilot study examined the effects of an educational intervention on anxiety in graduate students. The intervention included cognitive behavioral therapy (CBT) and mindfulness training, in addition to education about lifestyle health behaviors and study habits. First year graduate students in the UT Southwestern School of Health Professions were recruited for the pilot study. The study design included 4 educational sessions to provide education/training in CBT, mindfulness, lifestyle, and study habits. Subjects completed outcome measures before and after the intervention including the Depression Anxiety Stress Scale-21 (DASS-21) and a survey about subjects' behaviors in the domains targeted in the study. Results indicated a decrease in student distress in DASS-21 overall and individual subtest scores. The results suggest that a comprehensive intervention was successful in impacting the depression, anxiety, and overall stress levels of the involved students.

Parkinson’s disease affects the ability to walk often resulting in decreased independence and low quality of life. The purpose of this study was to examine differences in plantarflexor strength (PFS), gait speed, and step length in persons with Parkinson’s disease (PwP) and healthy peers using clinical measures. A secondary purpose was to examine the relationship between these gait components across disease severity. The study was a convenience sample of 71 PwP and 25 community healthy peers. Outcome measures included 10-Meter Walk, step length, and Calf-Raise Senior Test. PwP were separated into mild and moderate impairment groups using the Movement Disorders Society United Parkinson’s Disease Rating Scale Motor Subscale. Between group differences for gait speed (F _2,93 = 24.560, P = 0.000), step length (F _2,93 = 21.93, P = 0.000) and PFS (F _2,93 = 19.49, P < 0.000) were observed. Post hoc testing determined a difference (P < 0.00) in gait speed, step length, and PFS testing between moderate impairment versus healthy peers and mild impairment. A difference (P = 0.045) in step length and a trend towards significance (P = 0.064) for PFS was found between healthy peers and mild impairment group. This study revealed that PwP with mild impairment also have significant changes in step length and trends toward plantarflexor weakness without a significant difference in gait speed. These early changes may warrant early assessment and intervention to prevent decline. This study may bring clinical focus onto the plantarflexor and step length for early comprehensive assessment and treatment of gait and mobility for PwP.