Dmitri Katz

Dmitri Katz
The Open University (UK) · Department of Computing and Communications

Doctor of Philosophy

About

20
Publications
2,120
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84
Citations
Introduction

Publications

Publications (20)
Preprint
BACKGROUND The COVID-19 pandemic impacted older adults' social connections and increased loneliness, but also led to increased technology adoption, providing new opportunities to develop technology interventions to meet their social needs. Existing off the shelf social connection platforms do not contain facilities designed to break the cognitive c...
Article
Background: The global population is aging, leading to shifts in health care needs. In addition to developing technology to support physical health, there is an increasing recognition of the need to consider how technology can support emotional health. This raises the question of how to design devices that older adults can interact with to log the...
Article
Full-text available
The COVID-19 pandemic is worsening loneliness for many older people through the challenges it poses in engaging with their social worlds. Digital technology has been offered as a potential aid, however, many popular digital tools have not been designed to address the needs of older adults during times of limited contact. We propose that the Social...
Article
Co-design is a widely applied design process with well-documented values, including mutual learning and collective creativity. However, the real-world challenges of conducting multidisciplinary co-design research to inform the design of self-care technologies are not well established. We provide a qualitative account of a multidisciplinary project...
Preprint
Full-text available
Older adults face significant challenges in regards to the various stereotypes associated with ageing, which have consequences for their mental health and wellbeing. The COVID-19 pandemic has heightened these age-based stereotypes due to older adults' proportionally higher vulnerability to the virus. The present research explored how the pandemic h...
Preprint
Full-text available
Between 6-13% of older people report chronic loneliness, and at the start of the declaration of COVID-19 as a pandemic, concern was expressed about the impact of socially isolating viral containment measures on this population of people who are simultaneously medically vulnerable to the virus. Despite these alarms, there is little known about how l...
Preprint
Full-text available
The COVID-19 pandemic is increasing older people's existing challenges in engaging with their physical and social worlds, and is thereby likely to worsen their loneliness. Digital technology has been offered as a potential aid for social connectedness during social distancing/isolation. However, many popular digital communication tools have not bee...
Preprint
Full-text available
The COVID-19 pandemic is increasing older people's existing challenges in engaging with their physical and social worlds, and is thereby likely to worsen their loneliness. Digital technology has been offered as a potential aid for social connectedness during social distancing/isolation. However, many popular digital communication tools have not bee...
Preprint
Full-text available
In this paper we investigate the use of model-based reinforcement learning to assist people with Type 1 Diabetes with insulin dose decisions. The proposed architecture consists of multiple Echo State Networks to predict blood glucose levels combined with Model Predictive Controller for planning. Echo State Network is a version of recurrent neural n...
Preprint
BACKGROUND Physical activity trackers such as the Fitbit can allow clinicians to monitor the recovery of their patients following surgery. An important issue when analysing activity tracker data is to determine patients’ daily compliance with wearing their assigned device, following selection of an appropriate criterion to determine a valid day of...
Article
Full-text available
Background Physical activity trackers such as the Fitbit can allow clinicians to monitor the recovery of their patients following surgery. An important issue when analyzing activity tracker data is to determine patients’ daily compliance with wearing their assigned device, using an appropriate criterion to determine a valid day of wear. However, it...
Conference Paper
Full-text available
Type 1 diabetes is a potentially life-threatening chronic condition that requires frequent interactions with diverse data to inform treatment decisions. While mobile technologies such as blood glucose meters have long been an essential part of this process, designing interfaces that explicitly support decision-making remains challenging. Dual-proce...
Conference Paper
Full-text available
For those with chronic conditions, such as Type 1 diabetes, smartphone apps offer the promise of an affordable, convenient , and personalized disease management tool. However , despite significant academic research and commercial development in this area, diabetes apps still show low adoption rates and underwhelming clinical outcomes. Through user-...
Chapter
Hundreds of diabetes self-management apps are available for smart phones, typically using a diary or logging methodology. This paper investigates how well such approaches help participants to make sense of collected data. We found that, while such systems typically support data and trend review, they are ill suited to helping users understand compl...
Conference Paper
Type 1 Diabetes is a serious condition that demands careful balancing of lifestyle and medication to avoid serious complications. Current mobile health approaches for diabetes management are usually either automated insulin delivery systems or logbooks that depend on manual data collection and reflection. Both have their shortcoming such as loss of...
Conference Paper
High quality and affordable support for chronic health conditions is simultaneously one of the great challenges and opportunities for the application of ubiquitous computing technologies. Mobile networks of wearable connected devices and sensors have the potential to offer data driven personalized support and contextually aware real-time advice tha...
Conference Paper
Ubiquitous computing technologies have the potential to revolutionize the support of chronic health conditions: improving quality of life, reducing costs and optimizing health outcomes. Wearable networks of connected devices and sensors offer the prospect of personalized support and contextually aware advice, for those with specific chronic health...
Conference Paper
Full-text available
Hundreds of diabetes self-management apps are available for smart phones, typically using a diary or logging methodology. This paper investigates how well such approaches help participants to make sense of collected data. We found that, while such systems typically support data and trend review, they are ill suited to helping users understand compl...
Conference Paper
Full-text available
We looked at the real-world behavior of people with diabetes who had used a diabetes apps, in order to learn more about the effects of these products in their lives. Participants were interviewed about their views and experiences on diabetes and non-diabetes related apps. We found the majority of participants were no longer using apps as part of th...

Questions

Question (1)
Question
Am starting to collect a small set of diabetes relevant (T1) time series data (movement, blood glucose, sleep, etc.) Have talked to many people who are doing such research, but few people seem to know how to process the data.  Some have suggested ARIMA modelling, perhaps with ML for a variable window, but looking for any ideas or ideally someone who wants to co-author a research paper.  Please get in touch if you have ideas, know relevant papers, or are interested.   Thanks, Dmitri

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Projects

Projects (2)
Project
UK Hospitals often experience 'Black Alert' which means that scheduled operations must be cancelled and incoming patients turned away because all the beds are full. This can be caused by elderly patients being unable to be discharged and return to their home even though they no longer need clinical care but still need some level of minimal monitoring and assistance to live at home. We intend to use wearables, smart home, and other Internet of Things technologies to collect data from both people and devices and distribute the right data to the appropriate people at the level of detail that person needs. This may range from re-assuring adult children that their elderly parent is well to giving timely relevant data to specialist hospital clinicians so they can delivery targeted support to the patients who need it.
Project
This paper investigates how well such reflection based apps help people with diabetes make sense of collected data. We found that, while such systems typically support data and trend review, they are ill suited to helping users understand complex correlations in the data.