Wearable Sensors and Digital Platforms in Health

The JRC project on Trust in Digital Interactions (TRUDI) deals with the construction and renewal of confident and trusted relationships among institutions, corporations and citizens, addressed as a major and urgent issue to be solved. The present report examines relationships for nurturing trust between corporations and citizens. In this context the JRC investigated wearable sensors and digital platforms in health as an empirical case study of citizens' involvement in designing the values embedded in information systems and services as well as their implementation and management.

Personal wearable sensors could become the most powerful individual self-surveillance technology available to citizens. These ubiquitous, networked devices currently offer a breadth of capabilities to sense, digitally enhance and upload data of fine granularity such as body and health physiological functions, images, locations, sounds and motion. However, for wider adoption, it is crucial for citizens/end-users to rely on trusted and trustworthy implementations of wearable sensing technologies. Trusted systems are defined as systems functioning normally and delivering what it is promised and what the user expects, whereas trustworthiness is mostly objectively defined according to specific criteria and can be considered a metric for how much a system deserve the trust of its users (Kounelis et al. 2014). Therefore, in order to establish criteria for trust and trustworthiness, the present report aims to screen and analyse emerging solutions and architectures for verifying how these systems actually work; particularly, for checking whether functionalities, motivations and values embedded in their design hold the potential for user empowerment, equitable use and meaningful community participation in digital health platforms.

Download: Wearable Sensors and Digital Platforms in Health (.pdf, 11.223 KB).

Download from eHealthNews.eu: Wearable Sensors and Digital Platforms in Health (.pdf, 11.223 KB).

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...