Using combined accelerometer and heart rate data to estimate physical fitness

Description of the results of an experiment performed on a treadmill, in which heart rate and accelerometer parameters were combined to estimate physical fitness. This to ultimately develop a method to estimate physical fitness (VO2max) in the home environment of a patient

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Towards cancer rehabilitation at home: design of a telerehabilitation service for lung cancer patients

Although lung resection still provides the best long-term outcome for lung cancer, it is also associated with a considerable decay in physical and psychosocial health status. If not controlled, these symptoms can hamper postsurgical recovery, and lead to unscheduled healthcare use. This study aimed to determine the clinical relevance of and functional requirements for a telerehabilitation (TR) service to support recovery following lung resection. A modular remote monitoring and treatment service, consisting of an ambulant health monitoring module and an online exercise program, was developed to improve survivorship care following lung surgery through a user-centred design approach. Results from the requirement elicitation indicate positive intentions of both patients and professionals to use the RMT service as part of current care practice. In early phase evaluation usability and technical reliability of the developed system was found high. Future research should establish level of adoption of the system by the end users, as well as the effects on post-surgery recovery when integrated with current healthcare processes

Multidisciplinary Rehabilitation Treatment of Patients With Chronic Low Back Pain: A Prognostic Model for Its Outcome

Objectives: (1) To determine if treatment outcome in chronic low back pain can be predicted by a predefined multivariate prognostic model based on consistent predictors from the literature and (2) to explore the value of potentially prognostic factors further. Methods: Data were derived from a randomized controlled trial on the effect of a multidisciplinary rehabilitation program for chronic low back pain compared with usual care. The primary outcome measure was the Roland and Morris Disability Questionnaire and secondary outcomes were the Physical and Mental Component Summary Scales, derived from the Short Form Health Survey. Outcomes were expressed as the differences between baseline and follow-up (8 wk and 6 mo) values. A confirmatory and an exploratory model were defined. Baseline predictors included in the confirmatory model were pain intensity, work status, and Multidimensional Pain Inventory subgroup membership. The exploratory model included sick leave, compensation, depression, and fear-avoidance beliefs. Statistical analysis was performed using multiple linear regression analysis. Results: One hundred and sixty-three patients participated in the study. More pain was prognostic for more improvement in the rehabilitation group. No value was found for work status or the Multidimensional Pain Inventory subgroups. For the exploratory model, more depression and fear-avoidance beliefs predicted more improvement after rehabilitation. The explained variance ranged from 18.5% to 43.8% depending on the length of follow-up evaluation, the treatment group, and the outcome variable of interest. Discussion: The results of this study do not support the construction of a clinical prediction model. Future confirmative studies of homogeneous rehabilitation treatments and outcome measures are needed to shed more light on relevant prognostic factors

A telecare programme for self-management of COPD exacerbations and promotion of an active lifestyle

Objective: The Condition Coach (CoCo) is a technology-supported care programme for self-management of COPD exacerbations and for promotion of an active lifestyle. The objective is to investigate the added value of the telecare programme in terms of clinical changes compared to usual care, and in addition, to evaluate its use and acceptance. Intervention: CoCo consists of four modules: 1) activity coach for ambulant activity registration and real-time feedback to improve daily activity behaviour, 2) web-based exercise programme set up by the patient’s primary care physiotherapist, 3) self-treatment of COPD exacerbations via a triage diary on the webportal that provides advice to start medication when necessary, and 4) teleconsultation via the webportal. The latter is accessible for the patient and the involved primary and secondary care professionals. Methods: Twenty-nine COPD patients with ≥3 exacerbations or 1 hospitalization in the past 2 years are randomly assigned to either the intervention group (CoCo programme for 9 months) or the control group (usual care). Exacerbations, activity level, exercise capacity, symptom levels, health status and quality of life are assessed to evaluate clinical changes. Page hits on the webportal show the use of the programme, and the Unified Theory of Acceptance & Use of Technology explains usage behaviour. Results: Preliminary findings show that the webportal is highly accessed by the patients (90% of the days) with good usability (median 5.8, 7-point Likert). Remaining data will be collected in the upcoming months. Conclusions: The CoCo programme has potential as the intervention is highly used and accepted. Final results are expected in July 2013

Robust knowledge graph completion with stacked convolutions and a student re-ranking network

Knowledge Graph (KG) completion research usually focuses on densely connected benchmark datasets that are not representative of real KGs. We curate two KG datasets that include biomedical and encyclopedic knowledge and use an existing commonsense KG dataset to explore KG completion in the more realistic setting where dense connectivity is not guaranteed. We develop a deep convolutional network that utilizes textual entity representations and demonstrate that our model outperforms recent KG completion methods in this challenging setting. We find that our model's performance improvements stem primarily from its robustness to sparsity. We then distill the knowledge from the convolutional network into a student network that re-ranks promising candidate entities. This re-ranking stage leads to further improvements in performance and demonstrates the effectiveness of entity re-ranking for KG completion

How do COPD patients distribute their daily activities?

Better insight in daily activity behaviour of COPD patients is needed as a first step to enable a tailoring of their treatment. The objective of this study was to measure the daily activity of COPD patients and to compare the daily activity distribution with asymptomatic controls, using triaxial accelerometry

Co-creation of an ICT-supported cancer rehabilitation application for resected lung cancer survivors: design and evaluation

Background Lung cancer (LC) patients experience high symptom burden and significant decline of physical fitness and quality of life following lung resection. Good quality of survivorship care post-surgery is essential to optimize recovery and prevent unscheduled healthcare use. The use of Information and Communication Technology (ICT) can improve post-surgery care, as it enables frequent monitoring of health status in daily life, provides timely and personalized feedback to patients and professionals, and improves accessibility to rehabilitation programs. Despite its promises, implementation of telehealthcare applications is challenging, often hampered by non-acceptance of the developed service by its end-users. A promising approach is to involve the end-users early and continuously during the developmental process through a so-called user-centred design approach. The aim of this article is to report on this process of co-creation and evaluation of a multimodal ICT-supported cancer rehabilitation program with and for lung cancer patients treated with lung resection and their healthcare professionals (HCPs). Methods A user-centered design approach was used. Through semi-structured interviews (n = 10 LC patients and 6 HCPs), focus groups (n = 5 HCPs), and scenarios (n = 5 HCPs), user needs and requirements were elicited. Semi-structured interviews and the System Usability Scale (SUS) were used to evaluate usability of the telehealthcare application with 7 LC patients and 10 HCPs. Results The developed application consists of: 1) self-monitoring of symptoms and physical activity using on-body sensors and a smartphone, and 2) a web based physical exercise program. 71 % of LC patients and 78 % of HCPs were willing to use the application as part of lung cancer treatment. Accessibility of data via electronic patient records was essential for HCPs. LC patients regarded a positive attitude of the HCP towards the application essential. Overall, the usability (SUS median score = 70, range 35–95) was rated acceptable. Conclusions A telehealthcare application that facilitates symptom monitoring and physical fitness training is considered a useful tool to further improve recovery following surgery of resected lung cancer (LC) patients. Involvement of end users in the design process appears to be necessary to optimize chances of adoption, compliance and implementation of telemedicine

MyHealthFrame - design and evaluation of a minimally invasive communication platform for telemedicine services aimed at older adults

MyHealthFrame is a communication platform that telemedicine (and well-being) services can leverage to deliver motivational messages and notifications to their end-users. Instead of being a telemedicine service in itself, MyHealthFrame is a channel through which external services can reach their users to provide reminders or deliver simple information such as number of steps. To its end-users, MyHealthFrame is a tablet device which is designed to be perceived as a photoframe and can be immersed in the users’ living environment. In this paper, we describe the design and the preliminary assessment of the platform. The results of the feasibility study with five older adults (65+) are promising