Neurodegenerative disorders (NDDs) constitute an increasing global burden and can significantly impair an individual’s mobility, physical activity (PA), and independence. Remote monitoring has been difficult without relying on diaries/questionnaires which are more challenging for people with dementia to complete. Wearable global positioning system (GPS) sensors and accelerometers present a cost-effective and noninvasive way to passively monitor mobility and PA. In addition, changes in sensor-derived outcomes (such as walking behaviour, sedentary, and active activity) may serve as potential biomarkers of disease onset, progression, and response to treatment. We performed a systematic search across four databases to identify papers published within the past 5 years, in which wearable GPS or accelerometers were used to monitor mobility or PA in patients with common NDDs (Parkinson’s disease, Alzheimer’s disease, motor neuron diseases/amyotrophic lateral sclerosis, vascular parkinsonism, and vascular dementia). Disease and technology-specific vocabulary were searched singly, and then in combination, identifying 4985 papers. Following deduplication, we screened 3115 papers and retained 28 studies following a full text review. One study used wearable GPS and accelerometers, while 27 studies used solely accelerometers in NDDs. GPS-derived measures had been validated against current gold standard measures in one Parkinson’s cohort, suggesting that the technology may be applicable to other NDDs. In contrast, accelerometers are widely utilised in NDDs and have been operationalised in well-designed clinical trials.

Background: Sleep holds promise as a modifiable risk factor for neurodegenerative diseases and dementia. Clinical trials to modify sleep in people at risk of or in the early stages of dementia are needed. Monitoring natural sleep from home could support pragmatic and decentralized large-scale clinical trials. However, whether longitudinal sleep research can be successfully delivered remotely in this population has not been established yet. Objective: We investigated the feasibility of remote longitudinal research using wearable devices, web-based cognitive tasks, and a smartphone app to record sleep and cognition in older adults with mild cognitive impairment (MCI) or dementia. Methods: Older adults with MCI or dementia due to Alzheimer disease or Lewy body disease and cognitively healthy participants completed at-home sleep and circadian monitoring (digital sleep diaries, actigraphy, wearable sleep electroencephalography, and saliva samples) and digital cognitive assessments for 8 weeks. Feasibility outcomes included recruitment, retention, and data completeness. Results: In total, 41 participants consented (n=10, 24% participants with Alzheimer disease; n=11, 27% participants with Lewy body disease; and n=20, 49% controls). There were predominantly male and White British participants, with a mean age of 70.9 (SD 5.9) years. Retention was very high, with 40 (98%) participants completing 8 weeks of remote monitoring. Data completeness for sleep electroencephalography was 91% and ranged from 79% to 97% for all remote tasks and was overall high across all participant subgroups. In total, 30% (12/40) of participants reported receiving external support with completing study tasks. Conclusions: High rates of retention, data completeness, and data quality suggested that longitudinal multimodal sleep and cognitive profiling using novel and remote monitoring technology is feasible in older adults with MCI and dementia and healthy older adults, even without study partner support. Remote monitoring should be considered for mechanistic and interventional trials. Careful consideration should be given to how to ensure remote monitoring technologies reduce burden and enhance inclusivity, particularly in communities traditionally underserved by research and those with lower digital literacy. International Registered Report Identifier (IRRID): RR2-10.2196/52652

Background: Sleep disturbances are a potentially modifiable risk factor for neurodegenerative dementia secondary to Alzheimer disease (AD) and Lewy body disease (LBD). Therefore, we need to identify the best methods to study sleep in this population. Objective: This study will assess the feasibility and acceptability of various wearable devices, smart devices, and remote study tasks in sleep and cognition research for people with AD and LBD. Methods: We will deliver a feasibility and acceptability study alongside a prospective observational cohort study assessing sleep and cognition longitudinally in the home environment. Adults aged older than 50 years who were diagnosed with mild to moderate dementia or mild cognitive impairment (MCI) due to probable AD or LBD and age-matched controls will be eligible. Exclusion criteria include lack of capacity to consent to research, other causes of MCI or dementia, and clinically significant sleep disorders. Participants will complete a cognitive assessment and questionnaires with a researcher and receive training and instructions for at-home study tasks across 8 weeks. At-home study tasks include remote sleep assessments using wearable devices (electroencephalography headband and actigraphy watch), app-based sleep diaries, online cognitive assessments, and saliva samples for melatonin- and cortisol-derived circadian markers. Feasibility outcomes will be assessed relating to recruitment and retention, data completeness, data quality, and support required. Feedback on acceptability and usability will be collected throughout the study period and end-of-study interviews will be analyzed using thematic analysis. Results: Recruitment started in February 2022. Data collection is ongoing, with final data expected in February 2024 and data analysis and publication of findings scheduled for the summer of 2024. Conclusions: This study will allow us to assess if remote testing using smart devices and wearable technology is a viable alternative to traditional sleep measurements, such as polysomnography and questionnaires, in older adults with and without MCI or dementia due to AD or LBD. Understanding participant experience and the barriers and facilitators to technology use for research purposes and remote research in this population will assist with the development of, recruitment to, and retention within future research projects studying sleep and cognition outside of the clinic or laboratory. International Registered Report Identifier (IRRID): DERR1-10.2196/52652

Soft robotics is used in real-world clinical situations, including surgery, rehabilitation, and diagnosis. However, several challenges remain to make soft robots more viable, especially for clinical interventions such as improving sleep quality, which impacts physiological and mental health. This paper presents an autoethnographic account of the experience of sleeping with a companion robot (Somnox), which mimics breathing to promote better sleep. The study is motivated by the key author’s experience with insomnia and a desire to better understand how Somnox is used in different social contexts. Data were collected through diary entries for 16 weeks (8 weeks without, 8 weeks with) and analysed thematically. The findings indicate improved sleep and observations about the relationship developed with the companion robot, including emotional connection and empathy for the technology. Furthermore, Somnox is a multidimensional family companion robot that can ease stomach discomfort and stress, reduce anxiety, and provide holistic care.

Soft robotics offers significant promise for enhancing healthcare, providing benefits such as improved rehabilitation and daily assistance for both physical and mental health. Despite these advantages, its application in caring for older adults with neurodegenerative disorders (NDD) remains largely unexplored, even though the World Health Organization (WHO) identifies NDD as a major global health burden. This study investigates the perceptions of soft robotics among individuals with neurodegenerative diseases. Through focus groups, individual interviews, and co-design sessions with patients, clinicians, and caregivers, we explored usability, safety, concerns, emotional comfort, and design ideas for soft robotics. Our findings highlight the necessity for user-centered design to address these concerns, emphasizing the importance of creating multi-purpose technologies that can be used by both patients and caregivers to support each other and build relationships. This approach aims to enhance the acceptance and effectiveness of soft robotic technologies for this vulnerable population.