Requirements for 5G based telemetric cardiac monitoring

Thüemmler, Christoph; Rolffs, Claudia; Bollmann, Andreas; Hindricks, Gerhard; Buchanan, William J.

doi:10.1109/wimob.2018.8589139

Cited by 10 publications

(6 citation statements)

References 9 publications

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“…The emerging 5G technologies are potential to support smart healthcare applications, which fulfill the new requirements for healthcare such as improved QoS, better density and ultra-high reliability [233]. The integration of blockchain with 5G technologies can advance current healthcare systems and provide more performance benefits in terms of better decentralization, security, privacy [234], service efficiency and system simplification for lower operational costs [168]. Blockchain can incorporate with 5G technologies such as softwarization, cloud/edge computing for new smart healthcare services [235] as depicted in Fig.…”

Section: A Smart Healthcarementioning

confidence: 99%

Blockchain for 5G and beyond networks: A state of the art survey

Nguyen

Pathirana

Ding

et al. 2020

Journal of Network and Computer Applications

309

154

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Section: A Smart Healthcarementioning

confidence: 99%

Blockchain for 5G and beyond networks: A state of the art survey

Nguyen

Pathirana

Ding

et al. 2020

Journal of Network and Computer Applications

309

154

View full text Add to dashboard Cite

“…The study also shows that further privacy protection procedures and assets should be added to this type of architecture. Thuemmler et al [18] look into the 5G needs for telemetric cardiac monitoring by analysing data from a joint project on early geriatric rehabilitation of elderly patients in a care of the elderly department following minimal invasive and conservative treatment at a specialised cardiology unit in Leipzig, Germany. Individualized medicine, also known as Precision Medicine, is one of the fastest-growing industries, and the research shows that 5G will be able to fully support this trend.…”

Section: Related Workmentioning

confidence: 99%

The Key Criteria for Predicting Unusual Behavior in the Elderly With Deep Learning Models Under 5G Technology

Zamzami

2023

IEEE Access

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Deep learning algorithms and technology based on 5G networks may be able to help identify unusual behavior in elderly people. Because 5G networks have a lower latency and a greater bandwidth, it is possible to use more complex algorithms and larger data sets for training and detection in a real-time. On top of that, real-time analysis of the data gathered through in-home monitoring of the elderly can become much simpler to carry out with the help of 5G's potential to simplify the process. However, the system needs to be developed in a way that it considers the preferences of the most important criteria of elderly people, who have more requirements in terms of their living situation and the environment in which they live. Therefore, this study advocated using ''Decision Making Trial and Evaluation Laboratory'' (DEMATEL) to analyze the most crucial criteria (feature) required for creating a model for identifying odd behavior in elderly persons. Convolutional Neural Networks (CNNs) and Long Short-Term Memories (LSTMs) are adopted in detecting unusual behavior in the elderly after the analysis key criteria for predicting unusual behavior in the elderly by DEMATEL. The research established a concept by linking the SIMADL dataset with the dimension of elderly people's behavior and performed an experimental analysis using both CNN and LSTM. Performance evaluations show that the LSTM performs better in detecting unusual behavior in elderly persons with 96% accuracy. Depressive disorder is the most significant aspect of ageing that might lead to a typical unusual behavior in elderly persons, according to DEMATEL analysis.

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“…Lindkvist et al (2021) represented the wireless telemedicine technology distinguishing the outdoor and indoor situations utilizing the different encouraging technologies require for 5G, for example, huge multiple-input and multipleoutput (MIMO), high energy networking, body area, and cognitive radio networks. Thuemmler et al (2018) urged the telemetric cardiac tracking need which is dependent on real-world insights from an initial geriatric collaborative project on health maintenance of disabled people in elderly treatment units after minimally restrictive and aggressive diagnosis in a specialized cardiology department in Leipzig, Germany. Channel state estimation (CSE) is devised by Sodhro and Shah (2017) to present an algorithm for Quality of Experience (QoE) optimization dependent on transmission power control (TPC) in terms of a cycle service and a level of modulation.…”

Section: Related Workmentioning

confidence: 99%

Impact of telecommunication network on future of telemedicine in healthcare: A systematic literature review

al.¹

2022

Int. j. adv. appl. sci.

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Telemedicine is a combination of networking technologies and clinical data. The implementation of telemedicine has enhanced the regional distribution of resources, decreased the workforce of personnel, and shortened the space between healthcare staff and patients. Typically, the specialist doctors are settled and offer their services only in large urban areas. It is pertinent to reduce the imbalance of medical resources between urban and rural areas. The advent of telemedicine has the potential to address this issue. However, current telemedicine has its limitations in terms of data transfer and thus struggles to offer low latency in real-time applications. The recent developments in communication systems offer 5G and above connectivity. This study aims to analyze and synthesize the role of telecommunication networks for potential developments in the field of telemedicine. To this end, a systematic literature review has been conducted to address well-defined research questions. These questions aim to understand the working, flow, scope, and framework of the research area. This review provides an overview of telemedicine, the 5G-based telemedicine framework, and its comparison with the current system. It also discusses how the fast communication network (i.e., 5G and beyond 5G) with devices operating at low latency can revolutionize the healthcare system. Furthermore, a framework for future telemedicine has been provided along with potential application domains. Lastly, challenges and future directions beyond 5G have also been presented.

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Requirements for 5G based telemetric cardiac monitoring

Cited by 10 publications

References 9 publications

Blockchain for 5G and beyond networks: A state of the art survey

Blockchain for 5G and beyond networks: A state of the art survey

The Key Criteria for Predicting Unusual Behavior in the Elderly With Deep Learning Models Under 5G Technology

Impact of telecommunication network on future of telemedicine in healthcare: A systematic literature review

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