Patient Controlled, Privacy Preserving IoT Healthcare Data Sharing Framework

Healthcare data personally collected by individuals with wearable devices have become important sources of information for healthcare professionals and medical research worldwide. User-Generated Data (UGD) offers unique and sometimes fine-grained insight into the lived experiences and medical conditions of patients. The sensitive subject-matter of medical data can facilitate the exploitation and/or control of victims. Data collection in medical research therefore restricts access control over participant-data to the researchers. Therefore, cultivating trust with prospective participants concerned about the security of their medical data presents formidable challenges. Anonymization can allay such concerns, but at the cost of information loss. Moreover, such techniques cannot necessarily be applied on real-time streaming health data. In this paper, we aim to analyze the technical requirements to enable individuals to share their real-time wearable healthcare data with researchers without compromising privacy. An extension for delay-free anonymization techniques for real-time streaming health data is also proposed

Smart vest for respiratory rate monitoring of COPD patients based on non-contact capacitive sensing

In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic Obstructive Pulmonary Disease (COPD) patients during the rest period between respiratory rehabilitation exercises at home. To provide an extensible solution to the remote monitoring using this sensor and other devices, the design and preliminary development of an e-Health platform based on the Internet of Medical Things (IoMT) paradigm is also presented. In order to validate the proposed solution, two quasi-experimental studies have been developed, comparing the estimations with respect to the golden standard. In a first study with healthy subjects, the mean value of the respiratory rate error, the standard deviation of the error and the correlation coefficient were 0.01 breaths per minute (bpm), 0.97 bpm and 0.995 (p < 0.00001), respectively. In a second study with COPD patients, the values were -0.14 bpm, 0.28 bpm and 0.9988 (p < 0.0000001), respectively. The results for the rest period show the technical and functional feasibility of the prototype and serve as a preliminary validation of the device for respiratory rate monitoring of patients with COPD.Ministerio de Ciencia e Innovación PI15/00306Ministerio de Ciencia e Innovación DTS15/00195Junta de Andalucía PI-0010-2013Junta de Andalucía PI-0041-2014Junta de Andalucía PIN-0394-201

Open Humans:A platform for participant-centered research and personal data exploration

Background Many aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for human-participant research ranging from the social sciences to precision medicine. With this potential wealth of data comes practical problems (e.g., how to merge data streams from various sources), as well as ethical problems (e.g., how best to balance risks and benefits when enabling personal data sharing by individuals). Results To begin to address these problems in real time, we present Open Humans, a community-based platform that enables personal data collections across data streams, giving individuals more personal data access and control of sharing authorizations, and enabling academic research as well as patient-led projects. We showcase data streams that Open Humans combines (e.g., personal genetic data, wearable activity monitors, GPS location records, and continuous glucose monitor data), along with use cases of how the data facilitate various projects. Conclusions Open Humans highlights how a community-centric ecosystem can be used to aggregate personal data from various sources, as well as how these data can be used by academic and citizen scientists through practical, iterative approaches to sharing that strive to balance considerations with participant autonomy, inclusion, and privacy.publishedVersio

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

Dia-Continua: An Information System for Type 1 Diabetes Consultation. (Interoperability, Privacy, and Information Quality on a FHIR-Based Information System for Type 1 Diabetes Consultations based on Patient-Generated Health Data)

Patient-generated health data (PGHD) is required to monitor chronic conditions like Type 1 Diabetes (T1D). This data includes information from medical devices like insulin pumps and continuous glucose monitors and lifestyle insights from commercial wearables devices such as smartwatches. To improve the quality of medical consultations, we need a unified information system that can integrate PGHD. Designing such a system will pose several challenges. The system should be able to navigate through fragmented information and the complexities of various data formats, proprietary interfaces, and storage methods while ensuring robust security, privacy, and adherence to data ownership principles. It should also enable controlled data sharing with healthcare providers (HCPs) and external entities such as national registries and informal caregivers. This dissertation details designing, developing, and testing an information system for individuals with T1D. The project involved integrative research in health informatics, collaboration with international projects, and collaboration with experienced users and HCPs to address three research questions. These questions focused on interoperability, the security and privacy of the information collected, and the quality of the information presented during consultations. The result is Dia-Continua, a Fast Healthcare Interoperability Resources (FHIR)-based information system with a microservices architecture orchestrated through Kubernetes on an Infrastructure as a Service (IaaS) platform. The system integrates data from various diabetes management devices, questionnaires, and PGHD. Furthermore, using SMART on FHIR for authorization and authentication enables data sharing and reuse with national registries and informal caregivers. Eleven interviews with HCPs evaluated Dia-Continua's new functionalities and information quality. Despite the limitations due to proprietary device systems, the system was assessed positively by HCPs, highlighting the need for a system like Dia-Continua that includes physical activity, sleep, and stress in medical consultations. Dia-Continua is a significant step for a patient-centred model for consultations in T1D. Future work should expand the system's model to other chronic diseases.Utviklingen av medisinske konsultasjoner for kroniske tilstander, spesifikt Type 1 Diabetes (T1D), avhenger i stor grad av pasientgenererte helsedata (PGHD). Disse dataene inkluderer informasjon fra medisinsk utstyr slik som insulinpumper, CGM, samt livsstils data fra kommersielt utstyr som sensorer på smartklokker og smarte ringer. Et helhetlig informasjonssystem som kan integrere PGHD er nødvendig for å forbedre informasjonskvalitet under medisinske konsultasjoner. Imidlertid bør et slikt system være i stand til å la brukeren navigere gjennom fragmentert informasjon og komplekse heterogene dataformater, proprietære grensesnitt og lagringsmetoder, samtidig som systemet sikrer robust sikkerhet, personvern og ivaretakelse av prinsipper for eierskap til data. Systemet bør også muliggjøre kontrollert deling av data med helsepersonell og eksterne aktører slik som nasjonale registre (Noklus) og pasientens omsorgspersoner. Denne avhandlingen beskriver design, utvikling, testing og evaluering av et nytt informasjonssystem for T1D basert på pasientens egne data. Prosjektet har involvert ulike samarbeidspartnere og profesjoner, samt samarbeid med internasjonale prosjekter, erfarne brukere og HP for å adressere de tre forskningsspørsmålene i prosjektet. Ett av resultatene er systemet Dia-Continua, et Fast Healthcare Interoperability Resources (FHIR)-basert informasjonssystem med en Microservice arkitektur orkestrert gjennom Kubernetes på en infrastruktur som en tjenesteplattform (Azure). Systemet integrerer data fra ulike diabetesenheter, spørreskjemaer og andre sensorer. Videre, ved å bruke «SMART on FHIR» for autorisasjon og autentisering, muliggjøres deling og gjenbruk av data med nasjonale registre og uformelle omsorgspersoner. Elleve intervjuer med helsepersonell ble gjort for å evaluere Dia-Continua sine nye funksjonaliteter, samt dets informasjonskvalitet. Til tross for begrensningene på grunn av proprietære standarder, ble systemet positivt mottatt av HP. Informantene understreket behovet for et system som Dia-Continua som inkluderer fysisk aktivitet, søvn og stress i medisinske konsultasjoner. Dia-Continua er et betydelig skritt fram mot en pasientsentrert modell for konsultasjoner i T1D. Fremtidig arbeid bør utvide systemets modell til andre kroniske sykdommer

Central monitoring system for ambient assisted living

Smart homes for aged care enable the elderly to stay in their own homes longer. By means of various types of ambient and wearable sensors information is gathered on people living in smart homes for aged care. This information is then processed to determine the activities of daily living (ADL) and provide vital information to carers. Many examples of smart homes for aged care can be found in literature, however, little or no evidence can be found with respect to interoperability of various sensors and devices along with associated functions. One key element with respect to interoperability is the central monitoring system in a smart home. This thesis analyses and presents key functions and requirements of a central monitoring system. The outcomes of this thesis may benefit developers of smart homes for aged care

Digital Home Health During the COVID-19 Pandemic Challenges to Safety, Liability, and Informed Consent, and the Way to Move Forward

We argue that changing how postmarket studies are conducted and who evaluates them might mitigate some concerns over the agency’s increasing reliance upon RWE. Distributing the responsibility for designing, conducting, and assessing real world studies of medical devices and drugs beyond industry sponsors and the FDA is critical to producing – and acting upon – more clinically useful information. We explore how the DESI program provides a useful model for the governance of RWE today. We explain why the FDA’s Center for Devices and Radiological Health is the most promising site for a new DESI initiative inspired by the challenges of regulating drugs in the past.https://ideas.dickinsonlaw.psu.edu/book-contributions/1016/thumbnail.jp

A new framework architecture for next generation e-Health services

The challenge for fast and low-cost deployment of ubiquitous personalized e-Health services has prompted us to propose a new framework architecture for such services. We have studied the operational features and the environment of e-Health services and we led to a framework structure that extends the ETSI/Parlay architecture, which is used for the deployment of standardized services over the next generation IP networks. We expanded the ETSI/Parlay architecture with new service capability features as well as sensor, profiling and security mechanisms. The proposed framework assists the seamless integration, within the e-Health service structure, of diverse facilities provided by both the underlying communication and computing infrastructure as well as the patient's bio and context sensor networks. Finally, we demonstrate the deployment of a tele-monitoring service in smart home environment based on the proposed framework architecture