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• Journal article
  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.

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• 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.

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• Journal article
  Graham NSN, Cole JH, Bourke NJ, Schott JM, Sharp DJet al., 2023,

  Distinct patterns of neurodegeneration after TBI and in Alzheimer's disease

  , Alzheimer's and Dementia, Vol: 19, Pages: 3065-3077, ISSN: 1552-5260

  IntroductionTraumatic brain injury (TBI) is a dementia risk factor, with Alzheimer's disease (AD) more common following injury. Patterns of neurodegeneration produced by TBI can be compared to AD and aging using volumetric MRI.MethodsA total of 55 patients after moderate to severe TBI (median age 40), 45 with AD (median age 69), and 61 healthy volunteers underwent magnetic resonance imaging over 2 years. Atrophy patterns were compared.ResultsAD patients had markedly lower baseline volumes. TBI was associated with increased white matter (WM) atrophy, particularly involving corticospinal tracts and callosum, whereas AD rates were increased across white and gray matter (GM). Subcortical WM loss was shared in AD/TBI, but deep WM atrophy was TBI-specific and cortical atrophy AD-specific. Post-TBI atrophy patterns were distinct from aging, which resembled AD.DiscussionPost-traumatic neurodegeneration 1.9–4.0 years (median) following moderate-severe TBI is distinct from aging/AD, predominantly involving central WM. This likely reflects distributions of axonal injury, a neurodegeneration trigger.HighlightsWe compared patterns of brain atrophy longitudinally after moderate to severe TBI in late-onset AD and healthy aging.Patients after TBI had abnormal brain atrophy involving the corpus callosum and other WM tracts, including corticospinal tracts, in a pattern that was specific and distinct from AD and aging.This pattern is reminiscent of axonal injury following TBI, and atrophy rates were predicted by the extent of axonal injury on diffusion tensor imaging, supporting a relationship between early axonal damage and chronic neurodegeneration.

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• Journal article
  Parkinson M, Dani M, Fertleman M, Soreq E, Barnaghi P, Sharp D, Li LMet al., 2023,

  Using home monitoring technology to study the effects of traumatic brain Injury in older multimorbid adults: protocol for a feasibility study

  , BMJ Open, Vol: 13, ISSN: 2044-6055

  Introduction:The prevalence of Traumatic Brain Injury (TBI) among older adults is increasing exponentially. The sequelae can be severe in older adults and interacts with age-related conditions such a multimorbidity. Despite this, TBI research in older adults, is sparse. Minder, an in-home monitoring system using developed by the UK DRI Centre for Care Research and Technology, uses infra-red sensors and a bed mat to passively collect sleep and activity data. Similar systems have been used to monitor the health of older adults living with dementia. We will assess the feasibility of using this system to study changes in the health status of older adults in the early period post TBI.Methods and analysis:The study will recruit 15 inpatients (>60 years) with a moderate-severe TBI, who will have their daily activity and sleep patterns monitored using passive and wearable sensors over 6 months. Participants will report on their health during weekly calls, which will be used to validate sensor data. Physical, functional, and cognitive assessments will be conducted across the duration of the study. Activity levels and sleep patterns derived from sensor data will be calculated and visualised using activity maps. Within participant analysis will be performed to determine if participants are deviating from their own routines. We will apply machine learning approaches to activity and sleep data to assess whether these changes in these data can predict clinical events. Qualitative analysis of interviews conducted with participants, carers, and clinical staff will assess acceptability and utility of the system.Ethics and dissemination:Ethical approval for this study has been granted by the London - Camberwell St Giles Research Ethics Committee (REC number: 17/LO/2066). Results will be submitted for publication in peer review journals, presented at conferences and inform the design of a larger trial assessing recovery after TBI.

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• 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

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