Analysis of electrophysiological signals of the patients with chronic neck pain during sleep
| Autor: | Jiunn-Horng Kang, 康峻宏 |
|---|---|
| Rok vydání: | 2011 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 99 Chronic neck pain is defined as the duration of neck symptoms last for more than 6 months. It is estimated about 7.6% of general population having chronic neck pain. In addition to increased medical burden, neck pain is also one of the most frequent causes for lost workdays and pension claims. Although the specific pathomechanism of chronic neck pain is still unclear, identified risk factors include jobs pattern with high repetitive and monotonic movements, prior neck/shoulder injury, perceptive stress, low-pressure pain threshold to tenderness, and psychosocial factors. Some longitudinal study reported these patients may have poor prognosis and a significant ratio of patients had persist symptoms. The strong association between pain and sleep has been recognized. Most of patients who have underlying pain disorders suffer from sleep disturbance. Patients with pain conditions usually complain the difficulty to fall asleep, awake after sleep, reduced total sleep time and non-refreshing sleep. Sleep disturbance is associated with poor outcome of patients with chronic pain. Sleep can also directly modulate pain. Previous study showed the pain perception threshold can be altered after sleep deprivation in both normal subjects and patients with pain conditions. From previous polysomnography study, the patients with chronic pain had increased sleep fragmentation, decreased slow wave sleep, and alpha intrusion were reported. Some evidence supports the involvement of a dysautonomia is also involved in the pathogenesis of chronic pain. Worth noting, in patients with underlying pain, changes in autonomic balance could have primary origins, from an inherent dysfunctional central autonomic network, or secondary origins, as a response to pain or emotion associated with pain. Decreased vagal and increased sympathetic regulation may impart resistance to pain behavior. As a complex system, the biological system is usually inherently a non-linear and non-stationary system. Therefore, applying linear analysis to approach biological time series may be inadequate and miss some important information. In this thesis, we aim to investigate the presentations in sleep and autonomic system in the patients with chronic neck pain in a series of study. In addition, we used several non-linear methods to approach this topic. First, we found the heart rate variability (HRV) at resting status was significantly correlated with the level of disability in the patients with chronic neck pain. We suggest that HRV analysis may provide an objective tool to evaluate the severity of chronic neck pain. Furthermore, we conducted a standard PSG and concurrent linear and nonlinear analysis of HRV in the patients with chronic neck pain. We found the patients with chronic neck pain had lower approximate entropy and sample entropy of heart rate series during sleep compared to control group. However, the difference of HRV parameters in time and frequency domains between patients and controls was not significant. Hence, we suggest nonlinear analysis of HRV may be a more sensitive tool to detect the autonomic dysfunction in the patients with chronic neck pain. Our results also support that heart rate complexity is altered in the patients with chronic pain which implied these patients have altered baseline autonomic status even during sleep. We found that the patients with chronic neck pain had significantly lower entropy of electroencephalography (EEG) during sleep compared to controls, particularly in the awake, light sleep and overall sleep. In addition, a specific pattern of multiscale entropy can be found in the patients with chronic neck pain. The pathomechanism of our observation is still unknown. Previous studies demonstrated the EEG entropy is altered in several mental or neurological diseases. Decreased EEG entropy is associated with the disruption of neural network. Therefore, we hypothesize that underlying neural network could be altered during sleep in the patients with chronic pain. Non-linear analysis provides a powerful approach to investigate the biomedical signals. Nevertheless, further studies to evaluate the physiological basis and potential applications are still needed. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|