How Continuous Monitoring Changes the Interaction of Patients with a Mobile Telemedicine System

The use of continuous glucose monitor changes the way patients manage their diabetes, as observed in the increased number of daily insulin bolus, the increased number of daily BG measurements, and the differences in the distribution of BG measurements throughout the day. Continuous monitoring also increases the interaction of patients with the information system and modifies their patterns of use

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

A case study in Diabetes

Advances in sensors, mobile and embedded devices have made possible patient monitoring and provided medical treatments and other assistance in health care. Aging populations will benefit from reduced costs and improved health care through assisted living based on these technologies. In this paper we present a monitoring and control architecture allow control of a patient’s disease trough mobile and biometric devices. Our architecture is based on an Ambient Assisted Living control that provides different modules organized in a final application embedded in the mobile devices. This application is compounded by aspects like control of measurement, data obtained and representation, generation of suggestions, prevention, and education control. We have explored the architecture by developing a final application and implementing them in a prototype system. Our system shows the feasibility and opportunity of an open approach to ambient assisted living architecture.Advances in sensors, mobile and embedded devices have made possible patient monitoring and provided medical treatments and other assistance in health care. Aging populations will benefit from reduced costs and improved health care through assisted living based on these technologies. In this paper we present a monitoring and control architecture allow control of a patient’s disease trough mobile and biometric devices. Our architecture is based on an Ambient Assisted Living control that provides different modules organized in a final application embedded in the mobile devices. This application is compounded by aspects like control of measurement, data obtained and representation, generation of suggestions, prevention, and education control. We have explored the architecture by developing a final application and implementing them in a prototype system. Our system shows the feasibility and opportunity of an open approach to ambient assisted living architecture

An Architecture for Development of Ambient Assisted Living Applications: a Case Study in Diabetes

Advances in sensors, mobile and embedded devices have made possible patient monitoring and provided medical treatments and other assistance in health care. Aging populations will benefit from reduced costs and improved health care through assisted living based on these technologies. In this paper we present a monitoring and control architecture allow control of a patient’s disease trough mobile and biometric devices. Our architecture is based on an Ambient Assisted Living control that provides different modules organized in a final application embedded in the mobile devices. This application is compounded by aspects like control of measurement, data obtained and representation, generation of suggestions, prevention, and education control. We have explored the architecture by developing a final application and implementing them in a prototype system. Our system shows the feasibility and opportunity of an open approach to ambient assisted living architecture.Advances in sensors, mobile and embedded devices have made possible patient monitoring and provided medical treatments and other assistance in health care. Aging populations will benefit from reduced costs and improved health care through assisted living based on these technologies. In this paper we present a monitoring and control architecture allow control of a patient’s disease trough mobile and biometric devices. Our architecture is based on an Ambient Assisted Living control that provides different modules organized in a final application embedded in the mobile devices. This application is compounded by aspects like control of measurement, data obtained and representation, generation of suggestions, prevention, and education control. We have explored the architecture by developing a final application and implementing them in a prototype system. Our system shows the feasibility and opportunity of an open approach to ambient assisted living architecture

State-of-the-art and User Requirements of Blood Glucose Measurement: Devices, Software and Services.

Diabetes on jatkuvasti yleistyvä sairaus, joka vaatii yleisesti säännölliset verensokerin omamittaukset. Tämä Diplomityö tutkii verensokerimittauksen nykytilaa ja käyttäjätarpeita.. Erityisesti työ keskittyy verensokerimittareihin, verensokerimittauksen apuohjelmiin, sekä diabeteksen hoitosuosituksiin ja -käytäntöihin. Diplomityössä käsittellään lisäksi laadukkaan verensokerimittauksen määrittelyä Nykytilan analyysi perustuu valtaosin kirjallisuustutkimuksiin. Käyttäjätarpeiden kartoitus perustuu puolistrukturoituihin haastatteluihin. Haastatteluaineisto pohjautuu 8:aan haastatteluun, jossa haastateltiin kolmen eri käyttäjäryhmä edustajia: lääkäreitä, hoitajia ja diabeetikoita. Näiden käyttäjäryhmien käyttäjätarpeet ovat hyvin yhteneviä. Nykyiset verensokerimittauksen laitteet ja palvelut vastaavat hyvälaatuisen verensokerihallinnan vähimmäisvaatimuksiin. Nykyiset laitteet ja palvelut eivät vastaa Diplomityön esittelemiä vaativampia käyttäjätarpeita. Laitteiden ja palveluiden tulisi ola nykyistä kokonaisvaltaisempia ja integroituneita. Yksi verensokerimittauksen suurimmista haasteista on potilaan motivaatio mittausten laadukkaaseen läpivientiin. Potilaan motivaatioon vaikuttavien tekijöiden selvittäminen on yksi mielenkiintoinen jatkotutkimuksen aihe.Diabetes is an increasingly common illness that often requires regular measurement of Blood Glucose (BG). This Thesis discusses the state-of-the-art and user requirements of BG measurement, focusing on: BG meters, diabetes management software, and diabetes treatment guidelines and practices. Additionally, BG measurement quality definitions are discussed. The discussion on the state-of-the-art presented is primarily based on literature research. The requirements study is based on the results of a semi-structured interview of 8 subjects. The requirements of three user groups are discussed, i.e. doctors, nurses and diabetics. The requirements of the user groups are significantly similar. The current supply of BG measuring devices and services provides the bare minimum required for good quality BG measurement. The more advanced requirements elicited in this Thesis are mostly not met. The BG measuring devices and services are thus required to be more comprehensive and integrated. One of the key issues with BG measurement is motivating the diabetics to perform good quality measurements. Interesting topics for further research include the factors affecting patients’ motivation

Wearable continuous glucose monitoring sensors: A revolution in diabetes treatment

Worldwide, the number of people affected by diabetes is rapidly increasing due to aging populations and sedentary lifestyles, with the prospect of exceeding 500 million cases in 2030, resulting in one of the most challenging socio-health emergencies of the third millennium. Daily management of diabetes by patients relies on the capability of correctly measuring glucose concentration levels in the blood by using suitable sensors. In recent years, glucose monitoring has been revolutionized by the development of Continuous Glucose Monitoring (CGM) sensors, wearable non/minimally-invasive devices that measure glucose concentration by exploiting different physical principles, e.g., glucose-oxidase, fluorescence, or skin dielectric properties, and provide real-time measurements every 1–5 min. CGM opened new challenges in different disciplines, e.g., medicine, physics, electronics, chemistry, ergonomics, data/signal processing, and software development to mention but a few. This paper first makes an overview of wearable CGM sensor technologies, covering both commercial devices and research prototypes. Then, the role of CGM in the actual evolution of decision support systems for diabetes therapy is discussed. Finally, the paper presents new possible horizons for wearable CGM sensor applications and perspectives in terms of big data analytics for personalized and proactive medicine

Medical device design in context: a model of user–device interaction and consequences

The practice of evaluating interaction with devices is embedded in disciplines such as human-computer interaction and cognitive ergonomics, including concepts such as affordances, error analysis, skill, rule and knowledge based behaviour and decision making biases. This paper considers the way in which the approach that has been routinely applied to displays and control design within the control and transport domains can be transferred to the context of medical devices. The importance of considering the context in which medical devices are used and implemented is presented, and the need for a systems approach to medical device design is emphasised. Five case studies from medical device control and display design are presented as an aide to developing an understanding of the relationship between device design and resultant behaviours. On the basis of these case studies, four types of mediating factors (catalysts, enablers, facilitators and enhancers) are proposed and a model to describe the link between device design, user, context and consequences is presented

Enhancing system acceptance through user-centred design: Integrating patient generated wellness data

Gestational diabetes mellitus (GDM) is a condition that appears during pregnancy and is expected to be a temporary one. While patients are encouraged to manage it themselves, research findings indicate that GDM may negatively affect the foetus; in addition, there is an increased risk of women with GDM subsequently developing Type 2 diabetes. To alleviate the risks, women with GDM are advised to maintain a record of their diet and blood glucose levels and to attend regular clinical reviews. Rather than using a paper diary, women with GDM can maintain a record of their blood glucose level readings and other relevant data using a wellness mobile application (app). However, such apps are developed for general use and may not meet the specific needs of clinical staff (physicians, dietitians, obstetricians and midwives) involved in managing GDM; for example, an app may record glucose readings but not the details of a meal taken before or after the glucose reading. Second, the apps do not permanently store the data generated by the patient and do not support the transfer of these data to a clinical system or information portal. The mobile health (mHealth) system designed and developed in this research allows one to integrate different types of user generated wellness data into a centralised database. A user-centered design (UCD) approach informed by the technology acceptance model (TAM) was adopted. This paper investigates and evaluates the effectiveness of the approach with regard to facilitating system acceptance and future adoption through an early focus on enhancing system usefulness and ease of use. The functional system requirements of the proposed system were refined through a series of interviews with the perspective of clinical users; ease-of-use and usability issues were resolved through ‘think aloud’ sessions with clinicians and GDM patients