title: Effects of hemodialysis therapy on sit-to-walk characteristics in end stage renal disease patients.
abstract: 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.
authors.affiliation: School of Biomedical Engineering and Sciences, Virginia Tech Wake Forest University, Blacksburg, VA 24061, USA.
authors.forename: Rahul
authors.initials: R
authors.lastname: Soangra
authors.forename: Thurmon E
authors.initials: TE
authors.lastname: Lockhart
authors.forename: John
authors.initials: J
authors.lastname: Lach
authors.forename: Emaad M
authors.initials: EM
authors.lastname: Abdel-Rahman
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D001696:Biomechanical Phenomena; D001698:Biomedical Engineering; D005260:Female; D005684:Gait / Q000502:physiology; D006801:Humans; D007676:Kidney Failure, Chronic / Q000150:complications / Q000503:physiopathology* / Q000628:therapy*; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic; D011187:Posture / Q000502:physiology; D006435:Renal Dialysis / Q000009:adverse effects*; D016138:Walking / Q000502:physiology