Noninvasive Multimodal System to Detect Autonomic Dysreflexia in Individuals with Tetraplegia
Abstract
Rationale for Proposed Study: Bladder and bowel dysfunction represents a major challenge in the healthcare of persons with spinal cord injury (SCI) that affects their quality of life on a daily basis. A life-threatening syndrome that frequently accompanies insufficient emptying of the bladder or bowel as well as other noxious stimuli below the level of injury is autonomic dysreflexia (AD). AD occurs 85% of the time when a tetraplegic has an over-distended bladder, such as the result of an obstructed catheter. Other common triggers of AD are during regular urodynamic testing, bowel programs, sexual activity, pressure sores, or restrictive clothing in the lower extremities. Because many precipitants of AD are innocuous, it is extremely difficult to avoid the occurrence of AD. Currently the standard approach for managing AD is to train persons with SCI to recognize their symptoms and to promptly alleviate the AD trigger, which can be difficult to identify and frequently requires the assistance of a caregiver. The use of antihypertensive medication can result in chronic hypotension after AD subsides, which is problematic for tetraplegics with lower than normal resting blood pressures. There needs to be an accurate method of detecting AD during early onset for persons with SCI to understand AD is occurring and to quickly remove the trigger before symptoms escalate to a dangerous level. If the irritation is not removed, AD causes paroxysmal hypertension of over 200mm Hg, which may lead to seizures, hemorrhagic strokes, or even death. An automatic AD detection system is proposed to not only accurately recognize AD based on physiological changes in persons with SCI, but to rapidly detect AD before symptoms develop, such as sweating, headaches, and cold and clammy skin. One objective is to develop a more efficient, immediate AD detection machine learning model using data from spinal cord injured rats. The AD detection system will be programmed to detect increases in systolic blood pressure of 20 mmHg, which is the clinical threshold for the onset of AD. Secondly, the AD detection system will be translated to humans with SCI, incorporating a wearable array of multimodal, non-invasive physiological sensors that do not impede activities of daily living. There is currently no unencumbered method of continuously monitoring the onset of AD before symptoms become extreme and potentially dangerous, which can be used in research and clinical settings or for daily use at home and in one’s community. Contributions of the Proposed Project to SCI Research, Patient Care, and Quality of Life: In the highly cited survey by Anderson (2004), recovering bladder and bowel function and eliminating AD was ranked a greater priority by tetraplegics than regaining walking, normal sensation, or overcoming chronic pain. Only regaining arm and hand function and sexual function ranked higher. Better tools for managing AD are critical for improving independence and quality of life of individuals with SCI, which most commonly occurs as young adults. The development of AD symptoms (i.e., headaches, sweating, feeling of unease) can prevent the participation of persons with SCI in rehabilitation and exercise, sexual activity, certain medical tests, and other activities of daily living. An automatic AD early detection system would grant tetraplegics more time to identify and eliminate the AD trigger before it escalates to dangerous hypertensive levels. By combining the AD detection system with wireless mobile connectivity, caregivers can be automatically alerted when AD is occurring. This would enable tetraplegics greater autonomy to work, go to school, and participate in their communities knowing that if an AD episode occurs there will be emergency oversight. An AD early detection system will help those with new SCIs to learn to recognize early symptoms of AD before escalation. Severe episodes of AD produce an excessive release of catecholamines
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010725
Entities
People
- Bradley S Duerstock
Organizations
- Purdue University
- United States Army