Advances in smartphones and wearable biosensors enable real-time psychological, behavioural, and physiological data to be gathered in increasingly precise and unobtrusive ways. Thus, moment-to-moment information about an individual's moods, cognitions, and activities can be collected, in addition to automated data about their whereabouts, behaviour, and physiological states. In this report, we discuss the potential of these new mobile digital technologies to transform mental health research and clinical practice. By drawing on results from the INSIGHT research project, we show how traditional boundaries between research and clinical practice are becoming increasingly blurred and how, in turn, this is leading to exciting new developments in the assessment and management of common mental disorders. Furthermore, we discuss the potential risks and key challenges associated with applying mobile technology to mental health.
and Demosthenous, Andreas (2018) A high frame rate wearable EIT system using active electrode ASICs for lung respiration and heart rate monitoring. IEEE transactions on circuits and systems. I, Fundamental theory and applications, 65 (11). pp. 3810-3820.
A highly integrated, wearable electrical impedance tomography (EIT) belt for neonatal thorax vital multiple sign monitoring is presented. The belt has sixteen active electrodes. Each has an application specific integrated circuit (ASIC) connected to an electrode. The ASIC contains a fully differential current driver, a high-performance instrumentation amplifier (IA), a digital controller and multiplexors. The belt features a new active electrode architecture that allows programmable flexible electrode current drive and voltage sense patterns under simple digital control. It provides intimate connections to the electrodes for the current drive and to the IA for direct differential voltage measurement providing superior common-mode rejection ratio. The ASIC was designed in a CMOS 0.35-µm high-voltage technology. The high specification EIT belt has an image frame rate of 122 fps, a wide operating bandwidth of 1 MHz and multifrequency operation. It measures impedance with 98% accuracy and has less than 0.5 Ω and 1 o variation across all possible channels. The image results confirmed the advantage of the new active electrode architecture and the benefit of wideband, multifrequency EIT operation. The system successfully captured high quality lung respiration EIT images, breathing cycle and heart rate. It can also provide boundary shape information using an array of MEMS sensors interfaced to the ASICs.
As a result, the accelerometers are more versatile than bend sensors, which cannot be used on bigger cross-sections. The computational study estimates the optimal number of accelerometers required in order to generate an image reconstruction comparable to the use of a CT scan as the forward model. Furthermore, since the patient position is crucial to monitoring lung ventilation, the orientation of the phantoms is automatically detected by the accelerometer-based method.
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