Research into the ability to coordinate one’s movements with external cues has focussed on the use of simple rhythmic, auditory and visual stimuli, or interpersonal coordination with another person. Coordinating movements with a virtual avatar has not been explored, in the context of responses to temporal cues. To determine whether cueing of movements using a virtual avatar is effective, people’s ability to accurately coordinate with the stimuli needs to be investigated. Here we focus on temporal cues, as we know from timing studies that visual cues can be difficult to follow in the timing context. Real stepping movements were mapped onto an avatar using motion capture data. Healthy participants were then motion captured whilst stepping in time with the avatar’s movements, as viewed through a virtual reality headset. The timing of one of the avatar step cycles was accelerated or decelerated by 15% to create a temporal perturbation, for which participants would need to correct to, in order to remain in time. Step onset times of participants relative to the corresponding step-onsets of the avatar were used to measure the timing errors (asynchronies) between them. Participants completed either a visual-only condition, or auditory-visual with footstep sounds included, at two stepping tempo conditions (Fast: 400ms interval, Slow: 800ms interval). Participants’ asynchronies exhibited slow drift in the Visual-Only condition, but became stable in the Auditory-Visual condition. Moreover, we observed a clear corrective response to the phase perturbation in both the fast and slow tempo auditory-visual conditions. We conclude that an avatar’s movements can be used to influence a person’s own motion, but should include relevant auditory cues congruent with the movement to ensure a suitable level of entrainment is achieved. This approach has applications in physiotherapy, where virtual avatars present an opportunity to provide the guidance to assist patients in adhering to prescribed exercises.

Purpose This study assessed the feasibility of implementing a novel model of integrated prostate cancer care involving an online prostate cancer-specific holistic needs assessment (sHNA) and shared digital communication between patients and their healthcare professionals (HCPs). The sHNA produces a semi-automated care plan that is finalised in consultation between the patient and their practice nurse. Methods Men living with and beyond prostate cancer were invited to participate in a 9-month non-randomised cluster controlled feasibility study. The intervention group was asked to complete the sHNA on three occasions. Data were collected using Patient Reported Outcome Measures (PROMs) at baseline, 10 and 24 weeks, and 9 months. Outcomes included recruitment, retention, acceptability, and engagement with the sHNA and PROMs. Results Fourteen general practices (8 intervention and 6 control), and 41 men (29 intervention and 12 control) participated. Initial patient engagement with the sHNA was high, with all but one receiving practice nurse-led follow-up and an individualised care plan. The sHNA proved useful in identifying ‘red flag’ symptoms, and helping practice nurses decide when to seek further medical care for the patients. There was a high level of acceptability for patients and HCPs. However, integration of care did not occur as intended because of problems linking hospital and general practice IT systems. Conclusion While the study demonstrated the feasibility of implementing the sHNA, it did not meet the a priori progression criteria; as such, undertaking a definitive randomised controlled trial is not appropriate until the identified methodological and technical issues have been addressed.

Motivated by the aging trend, much effort is being invested into implementing ICT (Information and Communications Technology)-enabled systems to provide a better quality of life and support the independent living of older people. As a result, many systems, often labeled as eHealth or AAL (Ambient/Active Assisted Living), were developed over the years. In creating such systems, which very often serve various needs, different architectures have emerged. This work focuses on analyzing and comparing the work and architectures from seven (six of which are in progress) EU-funded healthcare projects, with a total budget of 126MEUR in which we participate. After establishing the theoretical foundation by defining core concepts, we give a brief background on architectures in eHealth and AAL. We elaborate on the chosen analysis method based on three established healthcare and AAL taxonomies we identified by performing a literature survey and the selected Reference Architecture Model (RAM). Since there is no standard way of describing architectures in the eHealth and AAL domain, we conducted the online survey during August and September 2020 and identified CREATE-IoT 3D RAM as the most appropriate option. We present a classification of selected projects based on established taxonomies and map projects’ architectures to CREATE-IoT 3D RAM, which we also propose as standard RAM for future digital healthcare and AAL projects. During our analysis, we identify the most common types of assistance: communication support, reminders, monitoring, and guidance to address health and communication issues. We conclude that proper ecosystems are critical for lowering entry barriers and facilitating sustainable solutions for smart and healthy living.

The potential of technology to aid integration of care delivery systems is being explored in a range of contexts across a variety of conditions in the United Kingdom. Prostate cancer is the most common cancer in UK men. With a 10-year survival rate of 84%, there is a need to explore innovative methods of care that are integrated between primary health care providers and specialist teams in order to address long-term consequences of the disease and its treatment as well as to provide continued monitoring for recurrence. Our aim was to test the feasibility of a randomized controlled trial to compare a model of prostate cancer continuing and follow-up care integration, underpinned by digital technology, with usual care in terms of clinical and cost-effectiveness, patient-reported outcomes, and experience. A first phase of the study has included development of an online adaptive prostate specific Holistic Needs Assessment system (HNA), training for primary care-based nurses, training of an IT peer supporter, and interviews with health care professionals and men with prostate cancer to explore views of their care, experience of technology, and views of the proposed intervention. In Phase 2, men in the intervention arm will complete the HNA at home to help identify and articulate concerns and share them with their health care professionals, in both primary and specialist care. Participants in the control arm will receive usual care. Outcomes including quality of life and well-being, prostate-specific concerns, and patient enablement will be measured 3 times over a 9-month period. Findings from phase 1 indicated strong support for the intervention among men, including those who had had little experience of digital technology. Men expressed a range of views on ways that the online system might be used within a clinical pathway. Health care professionals gave valuable feedback on how the output of the assessment might be presented to encourage engagement and uptake by clinical teams. Recruitment to the second phase of the study, the feasibility trial, commenced March 2017. To our knowledge, this study is the first in the United Kingdom to trial an online holistic needs assessment for men with prostate cancer, with data shared between patients and primary and secondary care providers. This study addresses recommendations in recent policy documents promoting the importance of data sharing and enhanced communication between care providers as a basis for care integration. We anticipate that this model of care will ultimately provide important benefits for both patients and the National Health Service. International Standard Randomized Controlled Trial Number (ISRCTN): 31380482; http://www.isrctn.com/ISRCTN31380482 (Archived by WebCite at http://www.webcitation.org/6s8I42u5N).

Recurrent miscarriage is a debilitating disorder associated with considerable physical and psychological morbidity. An estimated 50% of first trimester miscarriages remain unexplained. The aim of this study was to provide a personalised framework to guide the expectations of women experiencing recurrent miscarriage, with the ultimate goal of transforming clinical practice. We used real-world data from a UK longitudinal study of 1201 couples attending National Health Service (NHS) miscarriage clinics, with a history of previous miscarriages, comprising medical and obstetric history, results of investigations and pregnancy and neonatal outcome. We developed, parametrised, and validated predictive models for the probability that the next pregnancy is viable and for the time to next pregnancy. Time to next pregnancy separates couples into two groups, a group with subfertility, i.e., delay in conception, and a group with no significant delay in conception. We used Bayesian inference for the latter model. Trial registration number: The prospective data collections were pre-registered ISRCTN17732518; https://doi.org/10.1186/ISRCTN17732518. Predictive models of the time to pregnancy, the probability of the couple being subfertility and the probability of having a viable pregnancy can be parametrised from longitudinal study data. We identified several predictors for such models. In the viable pregnancy model, increased maternal age, higher Body Mass Index (BMI), having Polycystic Ovaries Syndrome (PCOS) and the number of previous miscarriages were associated with reduced odds of viable pregnancy. In contrast, having had previous live births increased the odds of a viable pregnancy. Model validation against a second external dataset gave an Area Under Curve (AUC) of 0.65 (95% Confidence Interval (CI): 0.55, 0.76). Of the 942 women referred to our recurrent miscarriage clinics and followed up over a period of 3 years, 10.7% (101) did not conceive during this time, indicating a potential subfertility problem. In the time to pregnancy model, increased maternal age, higher BMI, and smoking were associated with reduced likelihood of conception. Conversely, taking folic acid supplements and having a history of previous conceptions were associated with increased fertility. In our cohort, 53.4% (577 out of 1080 women) reported a pregnancy within 12 months. Additionally, 22.8% (277 out of 996 women who were followed up over a 2-year period) experienced a first pregnancy event in the second year. The area under the curve (AUC) for predicting pregnancy within 12 months was 0.60 (95% CI: 0.50–0.70) in an external validation using a second dataset. The pregnancy journey can be predicted on a personalised basis by integrating the validated models. We provide a framework for evidence-based management of women with miscarriage, comprising informed decision-making, including optimal referral to fertility services, and a tailored insight into fertility outcomes, thereby guiding expectations and providing psychological support. 10.13039/501100022291 Tommy's National Centre for Miscarriage Research .