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Inhabiting practices
Published in Gretchen Coombs, Andrew McNamara, Gavin Sade, Undesign, 2018
The Smart Heart necklace seeks to address the discomfort experienced by users who need to have cardiac monitoring. Current Holter monitors typically comprise small recorders worn on a sling or belt that can continuously collect data over a 24- to 48-hour period from two or three ECG leads attached to the chest. The primary users of cardiac monitors are in the 70–85 year age range, and they often require tests or treatments that require the use of adhesives. Within this age group, many people exhibit skin conditions ranging from decreased fluid retention, thinning, xerosis (dryness), eczema, irritation and itching (Barr, 2006). Regular, repeated use of ECG diagnostic systems using conventional wet electrodes may exacerbate these symptoms. Removal of tape and adhesives can, for instance, increase the risk of eczema (Avenel-audran et al., 2003; Konya et al., 2010) and, in severe cases, can result in skin tears (Reddy, 2008). In order to sidestep the need for adhesives, a key area of product innovation in the project has been the development of a conductive woven band to house the electronics for the necklace. This band, which has been created with a team of weavers, detects the ECG at the back of the neck and seamlessly delivers this information to the jewel structures at the front of the necklace, which house signal processing equipment and battery capacity, negating the requirement for stick-on electrodes and bulky technology.
Designing for Upper Torso and Arm Anatomy
Published in Karen L. LaBat, Karen S. Ryan, Human Body, 2019
Wearable technology for heart monitoring has a long history (Del Mar, 2005). After approximately 20 years of work on prototypes, Holter and Glassrock patented an ECG monitoring system to be worn during activity (Holter & Glassrock, 1965). Practical wearable heart monitoring devices, commonly called Holter monitors, were subsequently developed and marketed to provide ambulatory electrocardiography. Like many wearable medical products, ambulatory monitors were designed to accurately and efficiently capture medical information, with comfort and wearability as an afterthought.
Context-aware system for cardiac condition monitoring and management: a survey
Published in Behaviour & Information Technology, 2022
Godwin Okechukwu Ogbuabor, Juan Carlos Augusto, Ralph Moseley, Aléchia van Wyk
Health Monitoring Devices: As technology advances, modern smartphones and wearable devices are contributing immensely in the healthcare delivery process by assisting doctors and healthcare professionals to monitor patients at distance. Sensors embedded in these devices could be used to collect and aggregate a large amount of data from patient's biosignals, and analysed to assist doctors in decision-making. Several devices such as Fitbit, Mio Alpha 2 and Lifecard CF are available in the market for health monitoring. These gadgets range from portable, wearable to implantable tools. The most regularly used tool for cardiac condition monitoring is the Holter monitor. Holter monitor is a portable and continuous monitoring device used to generate and record ECG signals (Mittal, Movsowitz, and Steinberg 2011). Some of the modern Holter monitors allow users to wear the device while doing their normal activities and are capable of transmitting user's details to the physicians through mobile phones. Forkan and Hu (2016) proposed context-aware architecture that uses ECG sensor and FitBit to generate parameters to monitor older adult that lives alone and suffering cardiac disease. Sannino and De Pietro (2011) used Alive Heart Monitor(KardiaMobile), ECG sensor and accelerometer sensor to collect and aggregate different parameters for heart disease monitoring. Frederix et al. (2016) in their research used Mio Alpha 2 to collect user's details in order to monitor and support ischemic patients during rehabilitation. Some researchers such as Miao et al. (2015), and Kunnath et al. (2013), used smartphones to collect accelerometer data for activity recognition during the monitoring process. The raw accelerometer data were processed and used to train machine learning algorithms for human activity detection. In Table 2, we summarised different features of the available devices in the market for health monitoring. Among the monitoring devices listed in Table 2, Lifecard CF offers the advantage that it is capable of detecting Atrial fibrillation, heart attack, and heart disease while recording the ECG signals. However, none of these gadgets could provide a platform that generate contextual information, process, analyse and offer personalised recommendation to cardiac patient during rehabilitation. Figure 2 shows the (a) picture of Lifecard CF, (b) usages of Lifecard CF and (c) graphical representation of the ECG signals from the device.