A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis

By Alexandros Pantelopoulos, Nikolaos G. Bourbakis. 2010

2,316 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Medical & Health AI

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Citations in the corpus

Robust Aggregation for Federated Learning (2019, background): “The paradigm has found widespread applications ranging from mobile apps deployed on millions of devices [6, 87], to sensitive healthcare applications [40, 73].”
Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates (2019, background): “In response, there is a trend towards moving computation, including the training of machine-learning models, from cloud/datacenters to edge devices (Anguita et al., 2013; Pantelopoulos & Bourbakis, 2010).”
Federated Multi-Task Learning (2017, background): “Examples of potential applications include: learning sentiment, semantic location, or activities of mobile phone users; predicting health events like low blood sugar or heart attack risk from wearable devices; or detecting burglaries within smart homes [3, 37, 40].”
Federated Learning: Challenges, Methods, and Future Directions (2019, background): “te nature of the data and the limited connectivity of each device. Federated learning methods can help to train models that efﬁciently adapt to changes in these systems while maintaining user privacy [84, 98]. 1.1 Problem Formulation The canonical federated learning problem involves learning a singl”
A Survey of Healthcare Internet-of-Things (HIoT): A Clinical Perspective (2019, background): “These devices are connected to a WBAN, generally through an intermediate data aggregator such as a smartphone [36].”
Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges (2017, background): “It can also communicate with the remote healthcare facilities and caregivers, thus allowing the healthcare personnel to keep track of the overall physiological condition of the occupants and respond, if necessary, from a distant facility [16,20].”
Sensor-Based Activity Recognition (2012, background): “Over the past decade, sensor technologies, especially low-power, low-cost, high-capacity, and miniaturized sensors, wired and wireless communication networks [11]–[13],”
Review of Wearable Devices and Data Collection Considerations for Connected Health (2021, background): “Wearable devices can provide real-time feedback regarding a person’s health conditions; hence, they can provide an objective alternative to manage and monitor chronic disease progression, such as with the elderly, within rehabilitation, and for those with various disabilities [1].”
Sybil Attacks and Their Defenses in the Internet of Things (2014, background): “One of the most value-added functionalities of IoT is to sense the environments including the living environment [28] and human body [29]–[31], enabling users to interact with the physical world [32].”
Enabling Practical Backscatter Communication for On-body Sensors (2016, background): “The tiny energy budget combined with the simplicity of the hardware components needed to design backscatter-based sensors opens up a range of possibilities including micro-powered on-body sensors [52], miniature implantable sensors [51], thin and flexible wearables [39], and others.”
The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey (2015, neutral): “In addition to the industry IoT solutions, academic solutions in the wearable computing area are discussed in [26], [27].”
Deep ConvLSTM With Self-Attention for Human Activity Decoding Using Wearable Sensors (2020, background): “ECODING human activity has varied emerging applications for human wellbeing that include monitoring health [1], living condition [2], and daily activities[3], [4].”
Sensitive, high-strain, high-rate bodily motion sensors based on graphene-rubber composites. (2014, background): “Increasing interest surrounds wearable biosensors(10) which can monitor a range of biosignals including blood pressure, respiration rate and blood glucose levels.(2) Particularly important are wearable strain and motion sensors which can be used to monitor joint and muscle motion with the aim of sen”