Author :
Lanata, Antonio ; Valenza, Gaetano ; Nardelli, Mimma ; Gentili, Claudio ; Scilingo, Enzo Pasquale
Author_Institution :
Res. Center E. Piaggio, Univ. of Pisa, Pisa, Italy
Abstract :
This study discusses a personalized wearable monitoring system, which provides information and communication technologies to patients with mental disorders and physicians managing such diseases. The system, hereinafter called the PSYCHE system, is mainly comprised of a comfortable t-shirt with embedded sensors, such as textile electrodes, to monitor electrocardiogram-heart rate variability (HRV) series, piezoresistive sensors for respiration activity, and triaxial accelerometers for activity recognition. Moreover, on the patient-side, the PSYCHE system uses a smartphone-based interactive platform for electronic mood agenda and clinical scale administration, whereas on the physician-side provides data visualization and support to clinical decision. The smartphone collects the physiological and behavioral data and sends the information out to a centralized server for further processing. In this study, we present experimental results gathered from ten bipolar patients, wearing the PSYCHE system, with severe symptoms who exhibited mood states among depression (DP), hypomania(HM), mixed state (MX), and euthymia (EU), i.e., the good affective balance. In analyzing more than 400 h of cardiovascular dynamics, we found that patients experiencing mood transitions from a pathological mood state (HM, DP, or MX - where depressive and hypomanic symptoms are simultaneously present) to EU can be characterized through a commonly used measure of entropy. In particular, the SampEn estimated on long-term HRV series increases according to the patients´ clinical improvement. These results are in agreement with the current literature reporting on the complexity dynamics of physiological systems and provides a promising and viable support to clinical decision in order to improve the diagnosis and management of psychiatric disorders.
Keywords :
accelerometers; biomedical electrodes; biomedical telemetry; body sensor networks; computational complexity; data acquisition; data visualisation; decision support systems; diseases; electrocardiography; electronic data interchange; entropy; medical disorders; medical signal processing; neurophysiology; patient monitoring; piezoresistive devices; pneumodynamics; psychology; signal classification; smart phones; telemedicine; textile technology; HRV series monitoring; PSYCHE system; SampEn estimation; activity recognition; behavioral data collection; bipolar patient; cardiovascular dynamics; centralized server; clinical decision support; clinical scale administration; communication technology; complexity index; data processing; data transfer; data visualization; depression mood state; depressive symptom; disease management; electrocardiogram monitoring; electronic mood agenda; entropy measure; euthymia mood state; good affective balance; heart rate variability series monitoring; hypomania mood state; hypomanic symptom; information technology; long-term HRV series; mental disorder patient; mental health remission assessment; mixed mood state; mood transition; pathological mood state; patient clinical improvement; personalized wearable monitoring system; physiological data collection; physiological system complexity dynamics; piezoresistive sensor; psychiatric disorder diagnosis; psychiatric disorder management; respiration activity; smartphone-based interactive platform; symptom severity; t-shirt sensor embedding; textile electrode; time 400 h; triaxial accelerometer; Biomedical monitoring; Electrodes; Heart rate variability; Monitoring; Mood; Pathology; Bipolar patients; Heart Rate Variability (HRV); Wearable monitoring system; bipolar patients; complexity; heart rate variability (HRV); mental disorders; nonlinear analysis; sample entropy; sample entropy (SampEn); wearable monitoring system;
