Student Scholar SymposiumMain MenuWelcomeTuesday, May 5Main PageWednesday, May 6Main PageCenter for UG Excellence929059fe9a8db94662876b11cdef6e83b70e4c81
1media/red wave.jpg2020-04-13T23:43:56+00:00Center for UG Excellence929059fe9a8db94662876b11cdef6e83b70e4c8135Oral-Session Vplain2020-08-20T20:33:49+00:00Center for UG Excellence929059fe9a8db94662876b11cdef6e83b70e4c81
Evaluating Limits of Stability and Dynamic Balance of Idiopathic toe walking Children in Pre- and Post- Intervention with Smart Shoes Presenter(s): Nathaniel Addonizio, Lexi Nehls, Christopher Hoang, Michael Shiraishi Advisor(s): Dr. Rahul Soangra, Dr. Marybeth Grant-Beuttler Toe walking is a common walking pattern found in toddlers learning to walk. Toe walking can lead to an increase in instability due to a smaller base of support and tightness in the calves if it continues past childhood. In 2016, Faraldo-Garcia et al. conducted a study assessing the balance of healthy individuals. The researchers used the NeuroCom Balance Manager’s limits of stability (LOS) and sensory organization test (SOT) to assess a decrease of balance in the older subjects (Faraldo-Garcia et al., 2016). The LOS is an assessment that measures the maximum distance a person can lean in different directions while keeping their feet flat on the ground. In limits of stability, the subject moves their center of pressure to eight different locations and are scored on their ability to reach the target. A study conducted by Pletcher et al. used the NeuroCom Balance Manager’s SOT to assess postural stability in U.S special operations forces (Pletcher et al., 2017). The SOT is used to quantify impairments to postural stability by looking at the average center of gravity sway. In this study, we used the NeuroCom Balance Manager to compare the subjects’ (n=40) balance pre- and post- intervention using smart shoes embedded with sensors. The sensors use an algorithm to distinguish between toe walking and normal walking and when consecutive toe walking steps are recorded, a vibration is used to alert the wearer. We expect the smart shoe intervention to have a great impact by complementing the current intervention of physical therapy; the subject will be constantly alerted of toe walking throughout the day instead of only during visits with the PT. To assess the balance, we used the Balance Managers Software protocols including LOS, (SOT), adaption test (ADT), and motor control test. We expect to see an increase in balance and range of motion across all tests when comparing pre- and post-intervention data.
Effects of Muscle Fatigue on Motor Unit Recruitment Presenter(s): Shannon Toy, Tiffany Lubrino, Armond Gray, Christopher Hoang, Michael Shiraishi Advisor(s): Dr. Rahul Soangra Introduction:Muscle fatigue is the temporary decline of force and power skeletal muscles can produce due to muscle activity (Potvin & Fuglevand, 2017). This decline in muscle ability to perform over time is associated with the state of exhaustion following strenuous exercise, causing impaired activation of motor neurons that contracts muscle fibers - this can be further studied by understanding and quantifying the recruitment of motor units. A motor unit (MU) comprises of a neuron and the group of skeletal muscle fibers it innervates. As muscles are over-exerted, localized fatigue can be easily identified by exercise-associated muscle cramping (EAMC) (Schwellnus, Derman, & Noakes, 1997). The activation of individual MU can be monitored with the use of electromyography (EMG) sensors that quantify activation of muscles by translating electrical signals from muscle contractions into millivolts (mV). This study uses the Delsys Trigno EMG to identify the number of MU recruited during exercise and passes a high/low frequency filter to separate individual MU’s from all collected signals to observe the effects of fatigue through muscle performance by doing functional, gait, and postural tasks. Due to the body’s natural negative feedback system to protect the muscles, this study predicts the decrease of MU recruitment as the body experiences muscle fatigue. Material and Methods:Eight healthy college students participated in this IRB-approved fatigue study. Twenty-six reflective markers, four EMGs, and four Xsens Inertial Measurement Unit (IMU), were placed at various bony landmarks to obtain walking, heel raises and standing data. The functional trials were separated into pre- and post- fatigue tests. The subjects were fatigued using the Biodex Dynamometer by repeating 5 sets of 22 reps/min of unilateral plantar/dorsal-flexion ankle movement until 60% of maximum voluntary contractions (MVC) is achieved. The contribution of muscle fatigue to the anterior tibialis and the gastrocnemius was calculated by filtering high/low EMG frequencies to separate motor unit activation.