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• Conference paper
  Chen Z, Bannon A, Rapeaux A, Constandinou TGet al., 2021,

  Towards robust, unobtrusive sensing of respiration using UWB impulse Radar for the care of people living with dementia

  , 10th International IEEE-EMBS Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 866-871, ISSN: 1948-3546

  The unobtrusive monitoring of vital signals and behaviour can be used to gather intelligence to support the care of people living with dementia. This can provide insights into the person's wellbeing and the neurogenerative process, as well as enable them to continue to live safely at home, thereby improving their quality of life. Within this context, this study investigated the deployability of non-contact respiration rate (RR) measurement based on an Ultra-Wideband (UWB) radar System-on-Chip (SoC). An algorithm was developed to simultaneously and continuously extract the respiration signal, together with the confidence level of the respiration signal and the target position, without needing any prior calibration. The radar-measured RR results were compared to the RR results obtained from a ground truth measure based on the breathing sound, and the error rates were within 8% with a mean value of 2.5%. The target localisation results match to the radar-to-chest distances with a mean error rate of 5.8%. The tested measurement range was up to 5m. The results suggest that the algorithm could perform sufficiently well in non-contact stationary respiration rate detection.

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• Journal article
  Liu KY, Howard R, Banerjee S, Comas-Herrera A, Goddard J, Knapp M, Livingston G, Manthorpe J, O'Brien JT, Paterson RW, Robinson L, Rossor M, Rowe JB, Sharp DJ, Sommerlad A, Suarez-Gonzalez A, Burns Aet al., 2021,

  Dementia wellbeing and COVID-19: Review and expert consensus on current research and knowledge gaps

  , INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY, Vol: 36, Pages: 1597-1639, ISSN: 0885-6230
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  • Citations: 23
• Journal article
  Tiersen F, Batey P, Harrison MJC, Naar L, Serban A-I, Daniels SJC, Calvo RAet al., 2021,

  Smart home sensing and monitoring in households with dementia: user-centered design approach

  , JMIR Aging, Vol: 4, Pages: 1-20, ISSN: 2561-7605

  Background:As life expectancy grows, so do the challenges of caring for an ageing population. Older adults, including people with dementia, want to live independently and feel in control of their lives for as long as possible. Assistive technologies powered by Artificial Intelligence and Internet of Things devices are being proposed to provide living environments that support the users’ safety, psychological, and medical needs through remote monitoring and interventions.Objective:This study investigates the functional, psychosocial, and environmental needs of people living with dementia, their caregivers, clinicians, and health and social care service providers towards the design and implementation of smart home systems.Methods:We used an iterative user-centered design approach comprising nine sub-studies. First, semi-structured interviews (N = 9 people with dementia, 9 caregivers, 10 academic and clinical staff), ethnographic observations in clinics (N = 10 people with dementia, 10 caregivers, 3 clinical monitoring team members), and workshops (N = 35 pairs of people with dementia and caregivers, 12 health and social care clinicians) were conducted to define the needs of people with dementia, home caregivers and professional stakeholders in both daily activities and technology-specific interactions. Then, the spectrum of needs identified was represented via patient-caregiver personas and discussed with stakeholders in a workshop (N = 14 occupational therapists, 4 National Health Service pathway directors, 6 researchers in occupational therapy, neuropsychiatry and engineering) and two focus groups with managers of healthcare services (N = 8), eliciting opportunities for innovative care technologies and public health strategies. Finally, these opportunities were discussed in semi-structured interviews with participants of a smart home trial involving environmental sensors, physiological measurement devices, smart watches, and tablet-based chatbots and cognitive

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• Journal article
  Molero Y, Sharp DJ, Onofrio BMD, Larsson H, Fazel Set al., 2021,

  Psychotropic and pain medication use in individuals with traumatic brain injury-a Swedish total population cohort study of 240 000 persons

  , JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY, Vol: 92, Pages: 519-527, ISSN: 0022-3050
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  • Citations: 2
• Journal article
  Firouzi F, Farahani B, Daneshmand M, Grise K, Song JS, Saracco R, Wang LL, Lo K, Angelov P, Soares E, Loh P-S, Talebpour Z, Moradi R, Goodarzi M, Ashraf H, Talebpour M, Talebpour A, Romeo L, Das R, Heidari H, Pasquale D, Moody J, Woods C, Huang ES, Barnaghi P, Sarrafzadeh M, Li R, Beck KL, Isayev O, Sung N, Luo Aet al., 2021,

  Harnessing the power of smart and connected health to tackle COVID-19: IoT, AI, Robotics, and Blockchain for a better world

  , IEEE Internet of Things Journal, Vol: 8, Pages: 12826-12846, ISSN: 2327-4662

  As COVID-19 hounds the world, the common cause of finding a swift solution to manage the pandemic has brought together researchers, institutions, governments, and society at large. The Internet of Things (IoT), Artificial Intelligence (AI) — including Machine Learning (ML) and Big Data analytics — as well as Robotics and Blockchain, are the four decisive areas of technological innovation that have been ingenuity harnessed to fight this pandemic and future ones. While these highly interrelated smart and connected health technologies cannot resolve the pandemic overnight and may not be the only answer to the crisis, they can provide greater insight into the disease and support frontline efforts to prevent and control the pandemic. This paper provides a blend of discussions on the contribution of these digital technologies, propose several complementary and multidisciplinary techniques to combat COVID-19, offer opportunities for more holistic studies, and accelerate knowledge acquisition and scientific discoveries in pandemic research. First, four areas where IoT can contribute are discussed, namely, i) tracking and tracing, ii) Remote Patient Monitoring (RPM) by Wearable IoT (WIoT), iii) Personal Digital Twins (PDT), and iv) real-life use case: ICT/IoT solution in Korea. Second, the role and novel applications of AI are explained, namely: i) diagnosis and prognosis, ii) risk prediction, iii) vaccine and drug development, iv) research dataset, v) early warnings and alerts, vi) social control and fake news detection, and vii) communication and chatbot. Third, the main uses of robotics and drone technology are analyzed, including i) crowd surveillance, ii) public announcements, iii) screening and diagnosis, and iv) essential supply delivery. Finally, we discuss how Distributed Ledger Technologies (DLTs), of which blockchain is a common example, can be combined with other technologies for tackling COVID-19.

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