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Emerging Disruptive Technologies and Their Impact on Health Informatics
Published in Teena Bagga, Kamal Upreti, Nishant Kumar, Amirul Hasan Ansari, Danish Nadeem, Designing Intelligent Healthcare Systems, Products, and Services Using Disruptive Technologies and Health Informatics, 2023
The use of IoT-enabled devices help in enabling healthcare professionals, which will help in connecting patients proactively. The primary motive of using this technology is to keep track of medical equipment such as defibrillators, oxygen pumps, wheelchairs and nebulisers. Along with this, there are various monitoring devices, including glucose monitoring, hand hygiene monitoring, connected inhalers, remote patient monitoring, heart rate monitoring, depression and mood monitoring and ingestible sensors [22]. Similarly, blockchain technology also helps in monitoring patients’ actions which will further help in providing the right treatment to patients. The primary motive of using blockchain is to determine database management systems which further include robust data, unchangeable data, traceable data and provide access only to authorised users and protect the system from unauthorised users. It has been identified that smart contracts can be used for storing sensitive data and that data will be stored in encrypted form. This encrypted data is not visible to any normal user, and a decryption key will be used for accessing encrypted data.
The Use of Artificial Intelligence-Based Models for Biomedical Application
Published in Mohan Lal Kolhe, Kailash J. Karande, Sampat G. Deshmukh, Artificial Intelligence, Internet of Things (IoT) and Smart Materials for Energy Applications, 2023
Sharad Mulik, Nilesh Dhobale, Kanchan Pujari, Kailash Karande
As the conclusion of this study, AI has many opportunities in the healthcare industry, including reducing healthcare costs, reducing healthcare professionals’ workload, and easily giving more accurate diagnoses for various diseases. Due to the increase in the cost of the healthcare sector, AI is necessary and plays a vital role in cost reduction. Due to the shortage of nurses and healthcare professionals, so need to adopt an AI-based system for disease diagnosis. In developing countries, most of the population is poor, so they cannot take expensive treatment; in these countries, AI has overcome this problem. If a full implementation of AI in the healthcare sector occurs simultaneously, many costs will save and improve the quality of life. In developing countries, AI-based systems can implement patient health monitoring, primary diagnosis, VNA, and preventive health monitoring. The healthcare industry’s AI-based solution saves $150 billion by 2026 in global healthcare [3]. This study clearly shows that the AI-based system can impact the healthcare industry; hence, healthcare-related companies and research institutes should adopt AI fully.
Human Factors and Patient Self-Care
Published in Richard J. Holden, Rupa S. Valdez, The Patient Factor, 2021
Barrett S. Caldwell, Siobhan M. Heiden, Michelle Jahn Holbrook
Patient self-management programs, such as those proposed by the CCM, strongly indicate a framework where the patient is seen as a proactive and knowledgeable participant in their own healthcare performance. With experience and learning, the patient is expected to become even more skilled and capable of performing physical tasks as well as maintaining situation awareness to enhance their own health status (Bodenheimer et al., 2002a, 2002b). For example, patients may use self-management tools to monitor their own status (e.g., blood pressure monitoring) and keep a diary log to track values over time to share with their care team. If a patient perceives their blood pressure values are consistently above a pre-determined range, it may prompt them to take an action toward caring for themselves (e.g., adjusting exercise, diet, or contacting their clinician).
Graphene-based electrodes for ECG signal monitoring: Fabrication methodologies, challenges and future directions
Published in Cogent Engineering, 2023
Rimita Dey, Pravin Kumar Samanta, Ram Pramod Chokda, Bishnu Prasad De, Bhargav Appasani, Avireni Srinivasulu, Nsengiyumva Philibert
There is a growing emphasis on personalized healthcare instead of the traditional hospital-centric approach in the contemporary healthcare landscape. Individuals place significant importance on self-monitoring their health conditions, and wearable devices have emerged as a prominent technology (Bauer et al., 2014). These devices have also found considerable utility in sports applications. Cardiovascular diseases, including cardiac arrhythmia and coronary heart disease (CHD), remain a major global health concern, contributing significantly to human mortality (Deaton et al., 2011). In 2019, these diseases accounted for approximately 17.9 million deaths, comprising 32% of all global fatalities. One challenging aspect of these conditions is their often asymptomatic nature, making regular follow-up evaluations insufficient for early detection (Dupre et al., 2009). To address this issue, electrocardiography (ECG) has proven to be the most common and straightforward technique for recording the heart’s electrical activity (Arquilla et al., 2020). It is a crucial tool for diagnosing cardiovascular diseases (Bong et al., 2020; Liu et al., 2016; Verweij et al., 2020). Prolonged monitoring of ECG signals (Hong et al., 2019; Vuorinen et al., 2019) has shown promise in effectively detecting cardiovascular diseases, offering innovative clinical outcomes that facilitate accurate diagnosis and treatment (Pullano et al., 2022).
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
Parameters for health monitoring: There are different parameters such as heart rate, activity data, Blood pressure and ECG signals which can be considered when monitoring a patient. These parameters can assist physicians in decision-making and create avenue for proper monitoring and recommendations. Due to several symptoms of cardiac diseases, there is no consensus on parameters to monitor cardiac condition. As indicated in Table 1, researchers used different parameters for cardiac condition monitoring. Only in Sannino and De Pietro (2011) that involved cardiologists stated the reasons behind choosing those parameters. Considering the limited battery capacity of mobile devices, and given that patients monitoring involves continuous context acquisition from sensors, a context-aware system for cardiac monitoring should consider minimal number of possible parameters without putting the subject in danger. Furthermore, it is essential to state that different patients might suffer different kinds of cardiac conditions, it worth considering personalising context-aware system for patient monitoring in order to effectively monitor the subject based on his/her symptoms. For instance, a cardiac patient with high blood pressure might require that his/her blood pressure monitored alongside with other parameters, while the elderly patient might require that fall event is considered when choosing parameters for the subject. Table 1 present different research on context-aware system and parameters used for cardiac condition monitoring.
Designing interoperable telehealth platforms: bridging IoT devices with cloud infrastructures
Published in Enterprise Information Systems, 2020
Kostas M. Tsiouris, Dimitrios Gatsios, Vassilios Tsakanikas, Athanasios A. Pardalis, Ioannis Kouris, Thelma Androutsou, Marilena Tarousi, Natasa Vujnovic Sedlar, Iason Somarakis, Fariba Mostajeran, Nenad Filipovic, Harm op den Akker, Dimitrios D. Koutsouris, Dimitrios I. Fotiadis
Interoperability in telehealth platforms provides the ability to connect and exchange data from different information systems, devices and mobile applications, promoting more effective personalised interventions. This multidirectional sharing of information allows patients to access specialised information related to their condition provided by clinical experts (e.g. handouts, videos), while also being able to communicate directly with them via the telehealth platform (Powell et al. 2017). Furthermore, in-home monitoring using sensing devices can allow them to keep track of their condition, promoting self-engagement in medical interventions, since they will be provided with more detailed reports and enabling them to demonstrate and share their achievements with similar patients and family members. Clinicians are also met with new communication channels to share relevant patient knowledge and obtain feedback from other care providers, such as physiotherapists, formal and informal caregivers. Each specialist can enrich patient records with more details and further evaluations, which are directly shared to optimise patient management planning. Alarming signs can be quickly identified, allowing clinicians to initiate prompt interventions and, as patient monitoring can be continuous, progression rates and adherence can be estimated on the fly.