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Future health systems require the means to assess and track the neural and physiological function of a user over long periods of time, and in the community. Human body responses are manifested through multiple, interacting modalities – the mechanical, electrical and chemical; yet, current physiological monitors (e.g. actigraphy, heart rate) largely lack in cross-modal ability, are inconvenient and/or stigmatizing. We address these challenges through an inconspicuous earpiece, which benefits from the relatively stable position of the ear canal with respect to vital organs. Equipped with miniature multimodal sensors, it robustly measures the brain, cardiac and respiratory functions. Comprehensive experiments validate each modality within the proposed earpiece, while its potential in wearable health monitoring is illustrated through case studies spanning these three functions. We further demonstrate how combining data from multiple sensors within such an integrated wearable device improves both the accuracy of measurements and the ability to deal with artifacts in real-world scenarios.

Alzheimer's disease (AD) and obstructive sleep apnea (OSA) are highly prevalent, chronic conditions with intriguing, yet poorly understood epidemiological overlap. To date, the amount of OSA syndrome present in patients with AD across literature remains unknown. To address this question, we collected all available published clinical data and analyzed them through a quantitative meta-analytical approach. The results of our quantitative meta-analysis suggest that the aggregate odds ratio for OSA in AD vs. healthy control was 5.05 and homogeneous. This reflects that patients with AD have a five times higher chance of presenting with OSA than cognitively non-impaired individuals of similar age. Moreover, these data suggest that around half of patients with AD have experienced OSA at some point after their initial diagnosis. The additive impact of progressive changes in sleep quality and structure, changes in cerebral blood flow and the cellular redox status in OSA patients may all be contributing factors to cognitive decline and may further aggravate AD progression. It is hoped that the high OSA rate in AD patients, as suggested by the findings of our meta-analysis, might provide a sufficient clinical incentive to alert clinicians the importance of screening patients for OSA in AD, and stimulate further research in this area.

To date, EEG is the only quantifiable measure of the neural changes that define sleep. Although it is used widely for clinical testing, scalp-electrode EEG is costly and is poorly tolerated by sleeping patients. This was a pilot study to assess the agreement between EEG recordings obtained from a new ear-EEG sensor and those obtained simultaneously from standard scalp electrodes. Participants were four healthy men, 25 to 36 years of age. During naps, EEG tracings were recorded simultaneously from the ear sensor and from standard scalp electrodes. A clinical expert, blinded to the data collection, analyzed 30-second epochs of recordings from both devices, using standardized criteria. The agreement between scalp- and ear-recordings was assessed. We scored 360 epochs (scalp-EEG and ear-EEG), of which 254 (70.6%) were scored as non-REM sleep using scalp-EEG. The ear-EEG sensor had a sensitivity of 0.88 (95% confidence interval [CI], 0.82-0.92) and a specificity of 0.78 (95% CI, 0.70-0.84) in detecting N2/N3 sleep. The kappa coefficient between the scalp- and the ear-EEG was 0.65 (95% CI, 0.58-0.73). As a sleep monitor (all non-REM sleep stages vs. wake), the in-ear sensor had a sensitivity of 0.91 (95% CI, 0.87-0.94) and a specificity of 0.66 (95% CI, 0.56-0.75). The kappa coefficient was 0.60 (95% CI, 0.50-0.69). Substantial agreement was observed between recordings derived from a new ear-EEG sensor and conventional scalp electrodes on four healthy volunteers during daytime naps.

Obesity increases the risk and severity of sleep-disordered breathing. The degree to which excess body weight contributes to blood oxygen desaturation during hypopneic and apneic events has not been comprehensively characterized. To quantify the association between excess body weight and oxygen desaturation during sleep-disordered breathing. A total of 750 adult participants in the Wisconsin Sleep Cohort Study were assessed for body mass index (BMI) (kg/m(2)) and sleep-disordered breathing. The amount of Sa(O(2)), duration, and other characteristics of 37,473 observed breathing events were measured during polysomnography studies. A mixed-effects linear regression model estimated the association of blood oxygen desaturation with participant-level characteristics, including BMI, gender, and age, and event-level characteristics, including baseline Sa(O(2)), change in Vt, event duration, sleep state, and body position. BMI was positively associated with oxygen desaturation severity independent of age, gender, sleeping position, baseline Sa(O(2)), and event duration. BMI interacted with sleep state such that BMI predicted greater desaturation in rapid eye movement (REM) sleep than in non-REM sleep. Each increment of 10 kg/m(2) BMI predicted a 1.0% (SE, 0.2%) greater mean blood oxygen desaturation for persons in REM sleep experiencing hypopnea events associated with 80% Vt reductions. Excess body weight is an important predictor of the severity of blood oxygen desaturation during apnea and hypopnea events, potentially exacerbating the impact of sleep-disordered breathing in obese patients.

Background: The capacity to diagnose obstructive sleep apnoea (OSA) must be expanded to meet an estimated disease burden of nearly one billion people worldwide. Validated alternatives to the gold standard polysomnography (PSG) will improve access to testing and treatment. This study aimed to evaluate the diagnosis of OSA, using measurements of mandibular movement (MM) combined with automated machine learning analysis, compared to in-home PSG. Methods: 40 suspected OSA underwent single overnight in-home sleep testing with PSG (Nox A1, ResMed, Australia) and simultaneous MM monitoring (Sunrise, Sunrise SA, Belgium). PSG recordings were manually analysed by two expert sleep centres (Grenoble and London); MM analysis was automated. The Obstructive Respiratory Disturbance Index calculated from the MM monitoring (MM-ORDI) was compared to the PSG (PSG-ORDI) using intraclass correlation coefficient and Bland-Altman analysis. Receiver operating characteristic curves (ROC) were constructed to optimise the diagnostic performance of the MM monitor at different PSG-ORDI thresholds (5, 15 and 30 events/hour). Results: 31 patients were included in the analysis (58% men; mean (SD) age: 48 (15) years; BMI: 30.4 (7.6) kg/m2). Good agreement was observed between MM-ORDI and PSG-ORDI (median bias 0.00; 95% CI -23.25 to +9.73 events/hour). However, for patients with no or mild OSA, MM monitoring overestimated disease severity (PSG-ORDI 5-15: MM-ORDI overestimation +3.70 (95% CI -0.53 to +18.32) events/hour). In patients with moderate-severe OSA, there was an underestimation (PSG-ORDI >15: MM-ORDI underestimation -8.70 (95% CI -28.46 to +4.01) events/hour). ROC optimal cut-off values for PSG-ORDI thresholds of 5, 15, 30 events/hour were: 9.53, 12.65 and 24.81 events/hour, respectively. These cut-off values yielded a sensitivity of 88, 100 and 79%, and a specificity of 100, 75, 96%. The positive predictive values were: 100, 80, 95% and the negative predictive values 89, 100, 82%, respectively. Conclusion: The diagnosis of OSA, using MM with machine learning analysis, is comparable to manually scored in-home PSG. Therefore, this novel monitor could be a convenient diagnostic tool that can easily be used in the patients’ own home.

Background As a result of the COVID-19 pandemic Imperial College School of Medicine developed a structured volunteering programme involving 398 medical students, across eight teaching hospitals. This case study aims to explore the relationship between the processes, context, participant experiences and impacts of the programme so that lessons can be learned for future emergencies and service-learning programmes. Methods Using an illuminative approach to evaluation we invited all volunteers and supervisors to complete a mixed-methods survey. This explored differences in experience across demographics and contextual factors, correlations between aspects of induction, supervision and overall experience, and reviewed the impacts of the programme. Quantitative responses were statistically analysed and qualitative reflections were thematically coded to triangulate and explain quantitative findings. Follow up interviews were carried out to check back findings and co-create conclusions. Results We received responses from 61 students and 17 supervisors. Student participants described predominantly altruistic motivations and transformational changes to their professional identity driven by feeling included, having responsibility, and engaging in authentic workplace-based learning afforded by freedom from the assessed curriculum. They reported new perspectives on their future professional role within the multidisciplinary team and the value of workplace-based learning. They reported increases in wellbeing and self-esteem related to feeling included and valued, and positively contributing to service provision at a time of need. Significantly higher overall satisfaction was associated with a personalised induction, active supervision, earlier stage of training, and male gender. Gender-related differences were not explained through our data but have been reported elsewhere and warrant further study. The duration, intensity and type of role that volunteers performed was similar across demographics and did not appear to modulate their overall experience. Conclusions Whilst acknowledging the uniqueness of emergency volunteering and the survey response rate of 15% of volunteers, we suggest the features of a successful service-learning programme include: a learner-centred induction, regular contact with engaged and appreciative supervisors, and roles where students feel valued. Programmes in similar settings may find that service learning is most impactful earlier in medical students’ training and that students with altruistic motivations and meaningful work may flourish without formal outcomes and assessments.

Background The transition from secondary education to university challenges students’ learning strategies and academic performance, especially in self-directed, problem-based environments like medical school. Passive study methods often fail, while evidence-based strategies like retrieval practice, active learning, and growth mindset foster success. We evaluate a novel academic support programme (Academic Tutoring- (AT)) to enhance study skills, feedback use, and self-directed learning. Methods We developed and implemented AT for 1st year medical students, informed by the psychology of learning and behaviour change, AT aimed to support the development of self-efficacy and effective learning strategies during the transition into university. The programme involved meeting an Academic Tutor one-to-one once per term, and also as a group once per term. Academic Tutors engaged students in learner-centred conversations on study skills and professional development plus their wellbeing and welfare. A Likert questionnaire was designed to measure students’ responses to the experiences and perceived outcomes of AT. We also measured self-efficacy and mindset. Qualitative data was gathered through open-ended response items. Demographic and socioeconomic data was also gathered. Results AT positively impacted time-management and learning strategies. ‘Learning from successes and failures’ and ‘thinking how to achieve goals’ were associated with a growth mindset. All outcome measures were associated with self-efficacy. We noted that students from a widening participation (WP) background tended to show higher growth mindset relative to those from a non-WP background (r = -0.223, p = 0.08) and female students reported higher engagement with the programme (r-0.294, p  < 0.001). Students reported changes in behaviours and attitudes, and improved wellbeing. Conclusions Providing medical students with the tools to change their approach to work and revision can improve subjective reports of time management, implementation of successful learning strategies and wellbeing. Successful outcomes were associated with self-efficacy and mindset. These are modifiable constructs, and this work suggests that focussing conversations on self-efficacy and mindset may be beneficial for supporting positive behaviour change.

Many patients with obstructive sleep apnoea (OSA) remain undiagnosed and thus untreated, and in part this relates to delay in diagnosis. Novel diagnostic strategies may improve access to diagnosis. In a multicentre, randomised study, we evaluated time to treatment decision in patients referred for suspected OSA, comparing a mandibular movement (MM) monitor to respiratory polygraphy, the most commonly used OSA detection method in the UK. Adults with high pre-test probability OSA were recruited from both northern Scotland and London. 40 participants (70 % male, mean±SD age 46.8 ± 12.9 years, BMI 36.9 ± 7.5 kg/m2, ESS 14.9 ± 4.1) wore a MM monitor and respiratory polygraphy simultaneously overnight and were randomised (1:1) to receive their treatment decision based on results from either device. Compared to respiratory polygraphy, MM monitor reduced time to treatment decision by 6 days (median(IQR): 13.5 (7.0–21.5) vs. 19.5 (13.7–35.5) days, P = 0.017) and saved an estimated 29 min of staff time per patient.

The full impact of multisystem disease such as obstructive sleep apnoea (OSA) on regions of the central nervous system is debated, as the subsequent neurocognitive sequelae are unclear. Several preclinical studies suggest that its purported major culprits, intermittent hypoxia and sleep fragmentation, can differentially affect adult hippocampal neurogenesis. Although the prospective biphasic nature of chronic intermittent hypoxia in animal models of OSA has been acknowledged, so far the evidence for increased 'compensatory' neurogenesis in humans is uncertain. In a cross-sectional study of 32 patients with mixed severity OSA and 32 non-apnoeic matched controls inferential analysis showed bilateral enlargement of hippocampi in the OSA group. Conversely, a trend for smaller thalami in the OSA group was noted. Furthermore, aberrant connectivity between the hippocampus and the cerebellum in the OSA group was also suggested by the correlation analysis. The role for the ischemia/hypoxia preconditioning in the neuropathology of OSA is herein indicated, with possible further reaching clinical implications.

Background Imperial College School of Medicine, London UK, introduced a new curriculum in 2019, with a focus on the GMC outcomes for graduates, and pedagogy best practice. The new curriculum included formative assessments, named engagement and feedback assessments (EFAs), to support learning, and attainment in the summative examinations. The aims of this study were to assess the validity of EFAs and to determine whether they have utility as a modified form of programmatic assessment to inform decision-making regarding possible interventions by measuring and analysing attendance at and performance in these formative events. Methods Seven hundred and sixty-one students were included in the study and assessment results were included for academic years 2019/20 to 2020/21. Forty-one data points per student, (27 in Year 1 and 14 in Year 2) were used, to compare EFA scores with the summative performance. Attendance was monitored through engagement with the EFAs. Results Cohort 1 (enrolled 2019): In year 1, EFAs were associated with summative exam scores (overall r  = 0.63, p  < 0.001). Year 2, EFA scores were also associated with summative scores (overall r  = 0.57, p  < 0.001), including the clinical practical assessment ( r  = 0.45, p  < 0.001). Missing two or more EFAs was associated with a significant increase in the likelihood of failing one or more summative examinations in the first year (OR: 7.97, 95% CI 2.65–34.39) and second year (OR: 3.20, 95% CI 1.74–5.95). Missing more than two EFAs in their first year was also associated with a higher risk of failing a summative examination in the second year (OR: 2.47, 95% CI 1.33–4.71). Students who increased their attendance between year 1 and 2 fared better in summative assessment than those who maintained poor attendance, whereas those that reduced their attendance fared worse than those that maintained high attendance. Cohort 2 (enrolled 2020): Analysis of cohort 2 supported these findings and in this cohort missing two or more EFAs was again associated with an increased likelihood of failing a summative examination (OR = 4.00, 95% CI = 2.02–7.90). Conclusion Our EFA model has validity in predicting performance in summative assessments and can inform prospective interventions to support students’ learning. Enhancing attendance and engagement can improve outcomes.