A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy [Physical Therapy].

A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy [Physical Therapy].

A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy [Physical Therapy].

May 2011. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy [Physical Therapy].

A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy [Physical Therapy].

A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy [Physical Therapy].

A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy.

No description available.

Falls in older adults are linked with increased morbidity and mortality, and remain a major public health concern. Aging is associated with increased reliance on the visual system for postural control, termed “visual dependence”. Discordance between visual, vestibular and proprioceptive sensory information can lead to balance loss and falls. In addition to increased visual dependence (VD), older adults have more difficulty than younger adults in multi-tasking, performing simultaneous tasks (e.g. walk and talk), which may further increase fall risk. A common clinical test of physical function, the Timed Up and Go (TUG), requires the individual to stand from a seated position, walk forward, turn, walk back to the seat, turn and sit back down. Previous studies have explored the effect of multi-tasking during the TUG; however, the role of visual dependence and its interaction with multi-tasking on specific movement components of the TUG has not been deeply explored in the existing literature. The primary goal of this project was to understand the effects of aging and visual dependence on physical function as measured by the TUG. The three aims that guided this work are 1) to examine how aging affects performance metrics and movement components of the TUG (e.g. sit-to-stand, walking, turning, stand-to-sit) when simultaneously performing a motor task with or without with visual stimulation; 2) to examine how visual dependence affects performance metrics and movement components of the TUG when simultaneously performing a motor task with or without visual stimulation; and 3) to determine the effect of wearing a head mounted display (HMD) on performance metrics and movement components of the TUG in older and younger adults. Twelve younger adults (6 males) and sixteen older adults (8 males) participated in this work. They were further classified as sixteen visually independent adults (VI) (9 younger adults, 7 older adults, 9 males) and 12 visually dependent adults (VD) (3 young adults, 9 older adults, 5 males). Participants completed eight conditions: The dependent variables, measured using 6 inertial measurement unit sensors, included spatiotemporal variables of the TUG (total time, sub-component movement times, gait speed, step cadence during turning); three-dimensional peak trunk velocity (PTV) (i.e. around the mediolateral, vertical, and anteroposterior axes); acceleration range and jerk of sit-to-stand and stand-to-sit; and multitask cost. Multitask cost reflects the change in the motor behavior that occurs due to high attentional demanding conditions, with the lowest multitask cost reflecting poorer motor performance. The multitask cost was calculated as the percent change of each dependent variable in relation to the single task performance (i.e. TUG with no secondary task) in the third chapter. Our results demonstrated that the wear of HMD has an impact on TUG kinematics, regardless of adding a visual stimulus, more than holding a cup of water. Providing a visual stimulus decreased the PTV in walking and acceleration range in sit-to-stand. Particularly, presenting a visual stimulus in a pitch up rotation decreased the PTV in turning and increased the peak trunk velocity in stand-to-sit when compared to standard TUG. Older adults showed a decrease in the multitask cost (i.e. poorer performance) of turn and sit-to-stand time and the PTV in turning and a lower variability in trunk velocity in turning and sit-to-stand and the acceleration jerk in sit-to-stand and stand-to-sit compared to younger adults. Older adults who were visually dependent showed a lower mean and variability in the mediolateral and vertical acceleration range of sit-to-stand than older adults who were visually independent. Our results indicate that the wear of HMD has an impact on posture that should be taken into account in clinical research. Assessing the kinematics in turning and sitting-to-standing could be of a great interest for future studies that would include older adults with functional limitations (e.g. fallers versus non-fallers). Sit-to-stand motion, in particular, can differentiate older adults who are more sensitive to visual stimulation. / Physical Therapy

Muscle performance, particularly muscle fatigue and muscle recovery, impact an individual’s function and participation in activities of life. Most notably, older adults with medical co-morbidities experience impaired muscle performance from the natural aging process, cumulative effects of a sedentary lifestyle, or imposed bedrest, contributing to a significant reduction in health and quality of life.1 Exercise, particularly muscle strength, endurance, and power training, is considered “medicine” and often prescribed to improve the health and well-being of older adults, as well as younger adults.2 An appropriate exercise prescription requires knowledge of muscle fatigue and recovery in order to optimize the exercise program without preventing further muscle damage. Muscle fatigue and recovery have been characterized using frequency analyses of surface electromyography (sEMG) during muscle activation.3 Surface EMG measures electrical activity of a muscle, providing insight into muscle activation patterns.4 Conveniently, the sensors for sEMG are noninvasive, wireless, and compact, allowing capture of movement in a multitude of environments with minimal impact on typical movement patterns. By using sEMG to assess patterns during and after sustained isometric and dynamic knee extension, we hoped to determine baseline muscle fatigue and recovery patterns in subjects with no physical limitations for comparison with adults who are critically ill. The primary objective of this study is to improve our understanding of muscle fatigue and recovery in adults who are critically ill using sEMG technology and experimental procedures to be used in an intensive care unit (ICU) environment. We proposed to study muscle fatigue and recovery using sEMG through muscle activation analysis. The specific aims were to 1) measure time to task failure (TTTF) after a sub-maximal isometric contraction and dynamic contraction in adults who were healthy younger (HY), adults who were healthy older (HO) adults, and adults who were critically ill (CI); 2) measure time to muscle recovery after a sub-maximal isometric contraction and dynamic contraction in HY, HO, and CI; and 3) characterize a relationship between TTTF and time to recovery. Our hypotheses were that 1) CI would demonstrate a shorter TTTF than healthy subjects during an isometric contraction and dynamic contraction; 2) HY would demonstrate a shorter time to recovery, followed by HO, then CI after both an isometric contraction and dynamic contractions; and 3) there was no relationship between TTTF and time to recovery within group. Muscle fatigue and recovery were measured in the rectus femoris and vastus lateralis using sEMG. During a single 90 minute session, subjects participated in a 3 phase protocol: baseline strength measures, fatiguing contraction, and recovery contractions. The fatiguing contraction and subsequent recovery measures were performed twice – under isometric and dynamic conditions. Recovery measures were taken at termination (analysis point C), 1 minute (analysis point D), and ≥ 5 minutes (analysis point E). Sub-maximal indicated that the individual decided how long to keep their knee extended and stopped the contraction on their own at any time. Time to task failure and time to recovery amongst all 3 groups (HY, HO, and CI) were the basis for analysis of the dependent variables of sEMG – time (seconds) and median frequency (Fmed). After the isometric contraction, CI fatigued first, followed by HY, then HO. There was a statistically significant difference among TTTF and group (chi-squared with two degrees of freedom, p = 0.03). A Wilxocon rank sum test showed statistically significant differences between HY and HO (p = 0.03) and HO and CI (p = 0.02), but no statistically significant difference between HY and CI (p = 0.45). After the dynamic contraction, CI fatigued first, followed by HO, then HY. There was a statistically significant difference among TTTF and group (chi-squared with two degrees of freedom, p = 0.04). A Wilxocon rank sum test showed statistically significant difference between HY and CI (p = 0.02) and HO and CI (p = 0.02), but no statistically significant difference between HY and HO (p = 0.73). Chi-squared analysis between time to recovery and age group for both an isometric and dynamic contractions was performed. There was not a statistically significant difference for time to recovery between groups. After the isometric contraction, for the rectus femoris, all groups had a high percentage of subjects finish at analysis point E, with HY and HO having the same percentage recover at analysis point C and D, respectively. For the vastus lateralis, among the three groups, the HY had the highest percentage recovered at analysis point C. However, the largest percentage of HY subjects recovered at analysis point E. The HO and CI had the same percentage of subjects within group recover at analysis point D and E. After a dynamic contraction, for the rectus femoris, the highest percentage of HY and HO recovered at analysis point C, and CI at analysis point E. For the vastus lateralis, all groups had the highest percentage of subjects recover at analysis point C, with the HO and CI having all subjects recover before analysis point E. Our third hypothesis was that there was no relationship between TTTF and time to recovery within group. For an isometric contraction, the HY’s rectus femoris and vastus lateralis demonstrated a very weak – weak, positive correlation between TTTF and time to recovery. For a dynamic contraction, all, with the exception of HO’s vastus lateralis and CI’s rectus femoris, showed no association. HO’s vastus lateralis showed a weak, positive correlation, while the CI’s rectus femoris showed a moderate, negative correlation. None were statistically significant. This was the first study, to our knowledge, that studied muscle fatigue and muscle recovery using sEMG in patients with critical illness. From a study design perspective, the use of sEMG using Bluetooth technology was safe and feasible in the ICU setting. No adverse effects and excessive soreness were reported in CI. From a clinical perspective, despite a small sample size, CI showed comparable time to task failure and recovery time frames to HY and HO, indicating that perhaps patients do not need extensive five to ten minute rest breaks as commonly provided. Consideration to applied weight, as well as muscle fatigue and muscle recovery, should be given when designing an exercise program to appropriately tax the vulnerable muscle, while still preventing further muscle damage. Future research warrant a larger, more homogenous group of subjects, including similar diagnosis, severity of illness, and supplemental oxygenation. Secondly, efforts should be made to conduct testing in the ICU around comparable days to their length of stay. Thirdly, ideal testing should be performed prior to initiation of early mobility to capture a more authentic representation of muscle fatigue and recovery, resulting from ICUAW. All three modifications would assist in making results more generalizable. In addition, follow up sEMG analysis should be conducted to assess the effect of therapeutic interventions on muscle strength, fatigue, and recovery. Consideration must also be given to medical management, including sedatives and paralytics, as well as pH, which if in a more acidotic state, has greater hydrogen ions, which could influence fatigue. Lastly, being that sepsis is a primary admitting diagnosis and these individuals may present with muscle weakness that is not necessarily ICUAW, efforts should be made to assess if there is a difference in sEMG signals between muscle wasting from sepsis and ICUAW. / Physical Therapy