A Portable Low-Cost Respiration Rate Measurement System for Sleep Apnea Detection.

Continuous monitoring of breathing activity is vital in detecting respiratory-based diseases such as obstructive sleep apnea (OSA) and hypopnea. Sleep apnea (SA) is a potentially dangerous sleep problem that occurs when a person's breathing stops and begins periodically while they sleep. In addition, SA interrupts sleep, causing significant daytime sleepiness, weirdness, and irritability. This study aims to design a single inertial measurement unit (IMU) sensor-based system to analyze the respiratory rate of humans. The results of the developed system is validated with the Equivital Wireless Physiological Systems for different activities. Further, the experiment has been designed to identify the optimal sensor placement location for efficient respiration rate estimation during different activities. The performance of the developed model has been quantified using breathing rate estimation accuracy (% BREA) and mean absolute error (MAE). Among all sensor placement locations and activities combinations, a window size of 30sec resulted in the worst performance, whereas a window size ≥ 60sec resulted in a better performance (p-value<0.05). In addition, the performance of the model has been found consistent for window size ≥ 60sec (p-value>0.05). For activity 3 (lying straight), comparably similar performance, 0.52±0.24 and 0.52±0.12 (p-value>0.05) have been depicted by the sensor placement position 3 (Abdomen) and position 1 (chest), respectively. Further, for the other two activities, activity 1 (sitting and working) and activity 2 (sitting straight), the best performance has been depicted as 0.32±0.18, 0.49±0.21 respectively (p-value<0.05), by the sensor placement position 2 (left ribs). This research presents a reliable, cost-effective, portable respiration monitoring system that could detect SA during sleep.

Patients Prefer a Virtual Reality Approach Over a Similarly Performing Screen-Based Approach for Continuous Oculomotor-Based Screening of Glaucomatous and Neuro-Ophthalmological Visual Field Defects.

Standard automated perimetry (SAP) is the gold standard for evaluating the presence of visual field defects (VFDs). Nevertheless, it has requirements such as prolonged attention, stable fixation, and a need for a motor response that limit application in various patient groups. Therefore, a novel approach using eye movements (EMs) - as a complementary technique to SAP - was developed and tested in clinical settings by our group. However, the original method uses a screen-based eye-tracker which still requires participants to keep their chin and head stable. Virtual reality (VR) has shown much promise in ophthalmic diagnostics - especially in terms of freedom of head movement and precise control over experimental settings, besides being portable. In this study, we set out to see if patients can be screened for VFDs based on their EM in a VR-based framework and if they are comparable to the screen-based eyetracker. Moreover, we wanted to know if this framework can provide an effective and enjoyable user experience (UX) compared to our previous approach and the conventional SAP. Therefore, we first modified our method and implemented it on a VR head-mounted device with built-in eye tracking. Subsequently, 15 controls naïve to SAP, 15 patients with a neuro-ophthalmological disorder, and 15 glaucoma patients performed three tasks in a counterbalanced manner: (1) a visual tracking task on the VR headset while their EM was recorded, (2) the preceding tracking task but on a conventional screen-based eye tracker, and (3) SAP. We then quantified the spatio-temporal properties (STP) of the EM of each group using a cross-correlogram analysis. Finally, we evaluated the human-computer interaction (HCI) aspects of the participants in the three methods using a user-experience questionnaire. We find that: (1) the VR framework can distinguish the participants according to their oculomotor characteristics; (2) the STP of the VR framework are similar to those from the screen-based eye tracker; and (3) participants from all the groups found the VR-screening test to be the most attractive. Thus, we conclude that the EM-based approach implemented in VR can be a user-friendly and portable companion to complement existing perimetric techniques in ophthalmic clinics.