Imperial College London

Sarah Daniels

Faculty of MedicineDepartment of Brain Sciences

Clinical Director
 
 
 
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s.daniels

 
 
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Commonwealth BuildingHammersmith Campus

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Summary

 

Publications

Publication Type
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14 results found

Capstick A, Palermo F, Zakka K, Fletcher-Lloyd N, Walsh C, Cui T, Kouchaki S, Jackson R, Tran M, Crone M, Jensen K, Freemont P, Vaidyanathan R, Kolanko M, True J, Daniels S, Wingfield D, Nilforooshan R, Barnaghi Pet al., 2024, Digital remote monitoring for screening and early detection of urinary tract infections, npj Digital Medicine, Vol: 7, ISSN: 2398-6352

Urinary Tract Infections (UTIs) are one of the most prevalent bacterial infections in older adults and a significant contributor to unplanned hospital admissions in People Living with Dementia (PLWD), with early detection being crucial due to the predicament of reporting symptoms and limited help-seeking behaviour. The most common diagnostic tool is urine sample analysis, which can be time-consuming and is only employed where UTI clinical suspicion exists. In this method development and proof-of-concept study, participants living with dementia were monitored via low-cost devices in the home that passively measure activity, sleep, and nocturnal physiology. Using 27828 person-days of remote monitoring data (from 117 participants), we engineered features representing symptoms used for diagnosing a UTI. We then evaluate explainable machine learning techniques in passively calculating UTI risk and perform stratification on scores to support clinical translation and allow control over the balance between alert rate and sensitivity and specificity. The proposed UTI algorithm achieves a sensitivity of 65.3% (95% Confidence Interval (CI) = 64.3–66.2) and specificity of 70.9% (68.6–73.1) when predicting UTIs on unseen participants and after risk stratification, a sensitivity of 74.7% (67.9–81.5) and specificity of 87.9% (85.0–90.9). In addition, feature importance methods reveal that the largest contributions to the predictions were bathroom visit statistics, night-time respiratory rate, and the number of previous UTI events, aligning with the literature. Our machine learning method alerts clinicians of UTI risk in subjects, enabling earlier detection and enhanced screening when considering treatment.

Journal article

Raposo de Lima M, Horrocks S, Daniels S, Lamptey M, Harrison M, Vaidyanathan Ret al., 2023, The role of conversational AI in ageing and dementia care at home: a participatory study, 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Publisher: IEEE, ISSN: 1944-9437

Conversational artificial intelligence (AI) technologies hold significant promise to support the independence,well-being and safety of older adults living with frailty ordementia at home. However, further studies are needed toidentify: 1) valuable scenarios of support, 2) desired interactivefeatures, and 3) key challenges preventing long-term adoptionand utility in dementia care. In this paper, we explore therole of conversational technology in ageing and dementia careat home. Using a community-based participatory approach, weengaged 20 stakeholders, including people with lived experienceof dementia and frailty, to understand preferences, perceivedbenefits and concerns about integrating conversational AIinto daily routines at home. We uncovered key roles of thetechnology, including support of daily functions, health monitoring, risk mitigation, and cognitive stimulation. We emphasizethe need for adapting interactions to different levels of userfamiliarity and progression of cognitive decline. We addressthe importance of the communication style and suggest carefuluse of open-ended questions with target populations. We furtherdiscuss feasibility considerations to overcome current barriersto adoption. Overall, this work proposes design guidelines toshape the future conceptualization and development of naturallanguage interactions to support dementia care at home.

Conference paper

Parkinson M, Doherty R, Curtis F, Soreq E, Lai HHL, Serban A-I, Dani M, Fertleman M, Barnaghi PJ, Sharp DM, Li Let al., 2023, Using home monitoring technology to study the effects of traumatic brain injury in older multimorbid adults, Annals of Clinical and Translational Neurology, Vol: 10, Pages: 1688-1694, ISSN: 2328-9503

Internet of things (IOT) based in-home monitoring systems can passively collect high temporal resolution data in the community, offering valuable insight into the impact of health conditions on patients' day-to-day lives. We used this technology to monitor activity and sleep patterns in older adults recently discharged after traumatic brain injury (TBI). The demographics of TBI are changing, and it is now a leading cause of hospitalisation in older adults. However, research in this population is minimal. We present three cases, showcasing the potential of in-home monitoring systems in understanding and managing early recovery in older adults following TBI.

Journal article

Crook-Rumsey M, Daniels S, Abulikemu S, Lai H, Rapeaux A, Hadjipanayi C, Soreq E, Li L, Bashford J, Jeyasingh Jacob J, Gruia D-C, Lambert D, Weil R, Hampshire A, Sharp D, Haar Set al., 2023, Multicohort cross-sectional study of cognitive and behavioural digital biomarkers in neurodegeneration: the Living Lab study protocol, BMJ Open, Vol: 13, Pages: 1-9, ISSN: 2044-6055

Introduction and aimsDigital biomarkers can provide a cost-effective, objective, and robust measure forneurological disease progression, changes in care needs, and the effect of interventions.Motor function, physiology and behaviour can provide informative measures of neurologicalconditions and neurodegenerative decline. New digital technologies present an opportunityto provide remote, high-frequency monitoring of patients from within their homes. Thepurpose of the Living Lab study is to develop novel digital biomarkers of functionalimpairment in those living with neurodegenerative disease (NDD) and neurologicalconditions.Methods and analysisThe Living Lab Study is a cross-sectional observational study of cognition and behaviour inpeople living with NDDs and other, non-degenerative neurological conditions. Patients (n≥25for each patient group) with Dementia, Parkinson’s disease, Amyotrophic Lateral Sclerosis, Mild Cognitive Impairment, Traumatic Brain Injury, and Stroke along with controls (n≥60) willbe pragmatically recruited. Patients will carry out activities of daily living and functionalassessments within the living lab. The living lab is an apartment-laboratory containing afunctional kitchen, bathroom, bed and living area to provide a controlled environment todevelop novel digital biomarkers. The living lab provides an important intermediary stagebetween the conventional laboratory and the home. Multiple passive environmental sensors,internet-enabled medical devices, wearables, and EEG will be used to characterise functionalimpairments of NDDs and non-NDD conditions. We will also relate these digital technologymeasures to clinical and cognitive outcomes.Ethics and disseminationEthical approvals have been granted by the Imperial College Research Ethics Committee(reference number: 21IC6992). Results from the study will be disseminated at conferencesand within peer-reviewed journals.

Journal article

Su T, Calvo RA, Jouaiti M, Daniels S, Kirby P, Dijk D-J, Della Monica C, Vaidyanathan Ret al., 2023, Assessing a sleep interviewing chatbot to improve subjective and objective sleep: protocol for an observational feasibility study, JMIR Research Protocols, Vol: 12, Pages: 1-10, ISSN: 1929-0748

BACKGROUND: Sleep disorders are common among the aging population and people with neurodegenerative diseases. Sleep disorders have a strong bidirectional relationship with neurodegenerative diseases, where they accelerate and worsen one another. Although one-to-one individual cognitive behavioral interventions (conducted in-person or on the internet) have shown promise for significant improvements in sleep efficiency among adults, many may experience difficulties accessing interventions with sleep specialists, psychiatrists, or psychologists. Therefore, delivering sleep intervention through an automated chatbot platform may be an effective strategy to increase the accessibility and reach of sleep disorder intervention among the aging population and people with neurodegenerative diseases. OBJECTIVE: This work aims to (1) determine the feasibility and usability of an automated chatbot (named MotivSleep) that conducts sleep interviews to encourage the aging population to report behaviors that may affect their sleep, followed by providing personalized recommendations for better sleep based on participants' self-reported behaviors; (2) assess the self-reported sleep assessment changes before, during, and after using our automated sleep disturbance intervention chatbot; (3) assess the changes in objective sleep assessment recorded by a sleep tracking device before, during, and after using the automated chatbot MotivSleep. METHODS: We will recruit 30 older adult participants from West London for this pilot study. Each participant will have a sleep analyzer installed under their mattress. This contactless sleep monitoring device passively records movements, heart rate, and breathing rate while participants are in bed. In addition, each participant will use our proposed chatbot MotivSleep, accessible on WhatsApp, to describe their sleep and behaviors related to their sleep and receive personalized recommendations for better sleep tailored to their specific reasons for disrup

Journal article

Del Giovane M, Trender WR, Bălăeţ M, Mallas E-J, Jolly AE, Bourke NJ, Zimmermann K, Graham NSN, Lai H, Losty EJF, Oiarbide GA, Hellyer PJ, Faiman I, Daniels SJC, Batey P, Harrison M, Giunchiglia V, Kolanko MA, David MCB, Li LM, Demarchi C, Friedland D, Sharp DJ, Hampshire Aet al., 2023, Computerised cognitive assessment in patients with traumatic brain injury: an observational study of feasibility and sensitivity relative to established clinical scales, EClinicalMedicine, Vol: 59, ISSN: 2589-5370

Background:Online technology could potentially revolutionise how patients are cognitively assessed and monitored. However, it remains unclear whether assessments conducted remotely can match established pen-and-paper neuropsychological tests in terms of sensitivity and specificity.Methods:This observational study aimed to optimise an online cognitive assessment for use in traumatic brain injury (TBI) clinics. The tertiary referral clinic in which this tool has been clinically implemented typically sees patients a minimum of 6 months post-injury in the chronic phase. Between March and August 2019, we conducted a cross-group, cross-device and factor analyses at the St. Mary’s Hospital TBI clinic and major trauma wards at Imperial College NHS trust and St. George’s Hospital in London (UK), to identify a battery of tasks that assess aspects of cognition affected by TBI. Between September 2019 and February 2020, we evaluated the online battery against standard face-to-face neuropsychological tests at the Imperial College London research centre. Canonical Correlation Analysis (CCA) determined the shared variance between the online battery and standard neuropsychological tests. Finally, between October 2020 and December 2021, the tests were integrated into a framework that automatically generates a results report where patients’ performance is compared to a large normative dataset. We piloted this as a practical tool to be used under supervised and unsupervised conditions at the St. Mary’s Hospital TBI clinic in London (UK).Findings:The online assessment discriminated processing-speed, visual-attention, working-memory, and executive-function deficits in TBI. CCA identified two significant modes indicating shared variance with standard neuropsychological tests (r = 0.86, p < 0.001 and r = 0.81, p = 0.02). Sensitivity to cognitive deficits after TBI was evident in the TBI clinic setting under supervised and unsupervised conditions (F (15,555) = 3.9

Journal article

Kirby P, Lai H, Horrocks S, Harrison M, Wilson D, Daniels S, Calvo RA, Sharp DJ, Alexander CMet al., 2023, Patient and public involvement in technology-related dementia research: a scoping review (Preprint), JMIR Aging, Vol: 7, ISSN: 2561-7605

Background:Technology-related research for people with dementia and their carers often aims to enable people to remain living at home for longer and to prevent unnecessary hospital admissions. To develop research that is person-centred, effective and ethical, patient and public involvement (PPI) is necessary, though may be perceived as more difficult with this cohort. With recent and rapid expansions in health and care related technology, this review explores how, and with what impact, collaborations between researchers and stakeholders such as people with dementia have taken place.Objective:To describe approaches to PPI used to date in technology-related dementia research, along with the barriers and facilitators and impact of PPI in this area.Methods:A scoping review of literature relating to dementia, technology and patient and public involvement was conducted using Medline, PsycINFO, EMBASE and CINAHL. Papers were screened for inclusion by two authors. Data was then extracted using a pre-designed data extraction table by the same two authors; a third author supported resolution of any conflicts at each stage. Barriers and facilitators of undertaking PPI were then examined and themed.Results:Thirty-one papers were included for analysis. The majority (21/31) did not make clear distinctions between activities undertaken as PPI and activities undertaken by research participants, and as such their involvement did not fit easily into the NIHR definition of PPI. Most of this mixed involvement focused on the reviewing or evaluating of technology prototypes. A range of approaches was described, most typically using focus groups or co-design workshops. Nine studies described involvement at multiple stages through the research cycle, sometimes with evidence of sharing of decision-making power. Some studies commented on barriers or facilitators to effective PPI. Challenges identified were often around issues of working with people with significant cognitive impairments, and

Journal article

David MCB, Kolanko M, Del Giovane M, Lai H, True J, Beal E, Li LM, Nilforooshan R, Barnaghi P, Malhotra PA, Rostill H, Wingfield D, Wilson D, Daniels S, Sharp DJ, Scott Get al., 2023, Remote monitoring of physiology in people living with dementia: an observational cohort study, JMIR Aging, Vol: 6, Pages: 1-14, ISSN: 2561-7605

BACKGROUND: Internet of Things (IoT) technology enables physiological measurements to be recorded at home from people living with dementia and monitored remotely. However, measurements from people with dementia in this context have not been previously studied. We report on the distribution of physiological measurements from 82 people with dementia over approximately 2 years. OBJECTIVE: Our objective was to characterize the physiology of people with dementia when measured in the context of their own homes. We also wanted to explore the possible use of an alerts-based system for detecting health deterioration and discuss the potential applications and limitations of this kind of system. METHODS: We performed a longitudinal community-based cohort study of people with dementia using "Minder," our IoT remote monitoring platform. All people with dementia received a blood pressure machine for systolic and diastolic blood pressure, a pulse oximeter measuring oxygen saturation and heart rate, body weight scales, and a thermometer, and were asked to use each device once a day at any time. Timings, distributions, and abnormalities in measurements were examined, including the rate of significant abnormalities ("alerts") defined by various standardized criteria. We used our own study criteria for alerts and compared them with the National Early Warning Score 2 criteria. RESULTS: A total of 82 people with dementia, with a mean age of 80.4 (SD 7.8) years, recorded 147,203 measurements over 958,000 participant-hours. The median percentage of days when any participant took any measurements (ie, any device) was 56.2% (IQR 33.2%-83.7%, range 2.3%-100%). Reassuringly, engagement of people with dementia with the system did not wane with time, reflected in there being no change in the weekly number of measurements with respect to time (1-sample t-test on slopes of linear fit, P=.45). A total of 45% of people with dementia met criteria for hypertension. People with dem

Journal article

Seah CEL, Zhang Z, Sun S, Wiskerke E, Daniels S, Porat T, Calvo RAet al., 2022, Designing mindfulness conversational agents for people with early-stage dementia and their caregivers: thematic analysis of expert and user perspectives, JMIR Aging, Vol: 5, Pages: e40360-e40360, ISSN: 2561-7605

BACKGROUND: The number of people with dementia is expected to grow worldwide. Among the ways to support both persons with early-stage dementia and their caregivers (dyads), researchers are studying mindfulness interventions. However, few studies have explored technology-enhanced mindfulness interventions for dyads and the needs of persons with dementia and their caregivers. OBJECTIVE: The main aim of this study was to elicit essential needs from people with dementia, their caregivers, dementia experts, and mindfulness experts to identify themes that can be used in the design of mindfulness conversational agents for dyads. METHODS: Semistructured interviews were conducted with 5 dementia experts, 5 mindfulness experts, 5 people with early-stage dementia, and 5 dementia caregivers. Interviews were transcribed and coded on NVivo (QSR International) before themes were identified through a bottom-up inductive approach. RESULTS: The results revealed that dyadic mindfulness is preferred and that implementation formats such as conversational agents have potential. A total of 5 common themes were also identified from expert and user feedback, which should be used to design mindfulness conversational agents for persons with dementia and their caregivers. The 5 themes included enhancing accessibility, cultivating positivity, providing simplified tangible and thought-based activities, encouraging a mindful mindset shift, and enhancing relationships. CONCLUSIONS: In essence, this research concluded with 5 themes that mindfulness conversational agents could be designed based on to meet the needs of persons with dementia and their caregivers.

Journal article

Serban A-I, Soreq E, Barnaghi P, Daniels S, Calvo R, Sharp Det al., 2022, The effect of COVID-19 on the home behaviours of people affected by dementia, npj Digital Medicine, Vol: 5, ISSN: 2398-6352

The COVID-19 pandemic has dramatically altered the behaviour of most of the world’s population, particularly affecting the elderly, including people living with dementia (PLwD). Here we use remote home monitoring technology deployed into 31 homes of PLwD living in the UK to investigate the effects of COVID-19 on behaviour within the home, including social isolation. The home activity was monitored continuously using unobtrusive sensors for 498 days from 1 December 2019 to 12 April 2021. This period included six distinct pandemic phases with differing public health measures, including three periods of home ‘lockdown’. Linear mixed-effects modelling is used to examine changes in the home activity of PLwD who lived alone or with others. An algorithm is developed to quantify time spent outside the home. Increased home activity is observed from very early in the pandemic, with a significant decrease in the time spent outside produced by the first lockdown. The study demonstrates the effects of COVID-19 lockdown on home behaviours in PLwD and shows how unobtrusive home monitoring can be used to track behaviours relevant to social isolation.

Journal article

Wairagkar M, De Lima MR, Harrison M, Batey P, Daniels S, Barnaghi P, Sharp DJ, Vaidyanathan Ret al., 2021, Conversational artificial intelligence and affective social robot for monitoring health and well-being of people with dementia., Alzheimers & Dementia, Vol: 17 Suppl 11, Pages: e053276-e053276, ISSN: 1552-5260

BACKGROUND: Social robots are anthropomorphised platforms developed to interact with humans, using natural language, offering an accessible and intuitive interface suited to diverse cognitive abilities. Social robots can be used to support people with dementia (PwD) and carers in their homes managing medication, hydration, appointments, and evaluating mood, wellbeing, and potentially cognitive decline. Such robots have potential to reduce care burden and prolong independent living, yet translation into PwD use remains insignificant. METHOD: We have developed two social robots - a conversational robot and a digital social robot for mobile devices capable of communicating through natural language (powered by Amazon Alexa) and facial expressions that ask PwD daily questions about their health and wellbeing and also provide digital assistant functionality. We record data comprising of PwD's responses to daily questions, audio speech and text of conversations with Alexa to automatically monitor their health and wellbeing using machine learning. We followed user-centric development processes by conducting focus groups with 13 carers, 2 PwD and 5 clinicians to iterate the design. We are testing social robot with 3 PwD in their homes for ten weeks. RESULT: We received positive feedback on social robot from focus group participants. Ease of use, low maintenance, accessibility, assistance with medication, supporting with health and wellbeing were identified as the key opportunities for social robots. Based on responses to a daily questionnaire, our robots generate a report detailing PwD wellbeing that is automatically sent via email to family members or carers. This information is also stored systematically in a database that can help clinicians monitor their patients remotely. We use natural language processing to analyse conversations and identify topics of interest to PwD such that robot behaviour could be adapted. We process speech using signal processing and machine lear

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

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 (Preprint)

<sec> <title>BACKGROUND</title> <p>As life expectancy grows, so do the challenges of caring for an aging 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.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This study investigates the functional, psychosocial, and environmental needs of people living with dementia, their caregivers, clinicians, and health and social care service providers toward the design and implementation of smart home systems.</p> </sec> <sec> <title>METHODS</title> <p>We used an iterative user-centered design approach comprising 9 substudies. First, semistructured interviews (9 people with dementia, 9 caregivers, and 10 academic and clinical staff) and workshops (35 pairs of people with dementia and caregivers, and 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 (14 occupational therapists; 4 National Health Service pathway directors; and 6 researchers in occupational therapy, neuropsychiatry, and engineering) and 2 focus groups with managers of health care services (n=8), eliciting opportunities for innovat

Working paper

Woolham J, Freddolino P, Gibson G, Daniels Set al., 2021, Telecare at a crossroads? Finding researchable questions, Journal of Enabling Technologies, Vol: 15, Pages: 175-188

Purpose: This paper aims to report on a structured attempt to develop new directions for research into telecare. Current research evidence suggests that telecare in the UK is not optimally cost-effective and does not deliver better outcomes than more traditional forms of care and support. To address this problem, an analysis of expert opinion about future directions for research is provided. Design/methodology/approach: Two electronic surveys of UK based academic experts were conducted. Participants were drawn from a range of professional disciplines, including medicine, social care, occupational therapy and social policy and identified were by their contribution in this, or allied fields. The first survey included nine questions intended to identify at least one new research question that could form the basis of a funding proposal to the Nuffield Foundation, which provided “seedcorn” funding to support this work. Ten themes were identified following thematic analysis. The second survey asked participants to prioritise three of these themes. Findings: Key themes emerging as priority areas for future research were as follows: the role of assessment in ensuring technology deployment meets the needs of service users; ethical implications of technology and how these might be addressed in the future; and the use of end user co-production/co-creation approaches in the development of new assistive technologies and digital enabled care. Research limitations/implications: The findings are based on academic expert opinion; perspectives of practitioners, service users and family members are unrepresented. Practical implications: The findings of this study could contribute to development of new directions for telecare research, and future strategic funding decisions in this rapidly changing field. Originality/value: Evidence for sub-optimal outcomes for telecare requires new thinking. The authors are not aware of any other study that offers an analysis of expert opi

Journal article

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