Effect of Parkinson's Disease on Cardio-postural Coupling During Orthostatic Challenge.

Cardiac baroreflex and leg muscles activation are two important mechanisms for blood pressure regulation, failure of which could result in syncope and falls. Parkinson's disease is known to be associated with cardiac baroreflex impairment and skeletal muscle dysfunction contributing to falls. However, the mechanical effect of leg muscles contractions on blood pressure (muscle-pump) and the baroreflex-like responses of leg muscles to blood pressure changes is yet to be comprehensively investigated. In this study, we examined the involvement of the cardiac baroreflex and this hypothesized reflex muscle-pump function (cardio-postural coupling) to maintain blood pressure in Parkinson's patients and healthy controls during an orthostatic challenge induced via a head-up tilt test. We also studied the mechanical effect of the heart and leg muscles contractions on blood pressure. We recorded electrocardiogram, blood pressure and electromyogram from 21 patients with Parkinson's disease and 18 age-matched healthy controls during supine, head-up tilt at 70°, and standing positions with eyes open. The interaction and bidirectional causalities between the cardiovascular and musculoskeletal signals were studied using wavelet transform coherence and convergent cross mapping techniques, respectively. Parkinson's patients displayed an impaired cardiac baroreflex and a reduced mechanical effect of the heart on blood pressure during supine, tilt and standing positions. However, the effectiveness of the cardiac baroreflex decreased in both Parkinson's patients and healthy controls during standing as compared to supine. In addition, Parkinson's patients demonstrated cardio-postural coupling impairment along with a mechanical muscle pump dysfunction which both could lead to dizziness and falls. Moreover, the cardiac baroreflex had a limited effect on blood pressure during standing while lower limb muscles continued to contract and maintain blood pressure via the muscle-pump mechanism. The study findings highlighted altered bidirectional coupling between heart rate and blood pressure, as well as between muscle activity and blood pressure in Parkinson's disease. The outcomes of this study could assist in the development of appropriate physical exercise programs to reduce falls in Parkinson's disease by monitoring the cardiac baroreflex and cardio-postural coupling effect on maintaining blood pressure.

Early Detection of Parkinson's Disease Using Center of Pressure Data and Machine Learning.

Parkinson's disease (PD) is a progressive neurodegenerative disorder resulting in abnormal body movements. Postural instability is one of the primary motor symptoms of PD and contributes to falls. Measurement of postural sway through center of pressure (COP) data might be an objective indicator of Parkinson's disease. The goal of this work is to use machine learning to evaluate if different features of postural sway can differentiate PD patients from healthy controls. Time domain, frequency domain, time-frequency, and structural features were extracted from COP data collected from 19 PD patients and 13 healthy controls (HC). The calculated parameters were input to various machine-learning models to classify PD and HC. Random Forest outperformed the rest of the classifiers in terms of accuracy, false negative rate, F1-score, and precision. Time domain features had the best performance in differentiating PD from HC compared to other feature groups.