20,630 research outputs found
CoachAI: A Conversational Agent Assisted Health Coaching Platform
Poor lifestyle represents a health risk factor and is the leading cause of
morbidity and chronic conditions. The impact of poor lifestyle can be
significantly altered by individual behavior change. Although the current shift
in healthcare towards a long lasting modifiable behavior, however, with
increasing caregiver workload and individuals' continuous needs of care, there
is a need to ease caregiver's work while ensuring continuous interaction with
users. This paper describes the design and validation of CoachAI, a
conversational agent assisted health coaching system to support health
intervention delivery to individuals and groups. CoachAI instantiates a text
based healthcare chatbot system that bridges the remote human coach and the
users. This research provides three main contributions to the preventive
healthcare and healthy lifestyle promotion: (1) it presents the conversational
agent to aid the caregiver; (2) it aims to decrease caregiver's workload and
enhance care given to users, by handling (automating) repetitive caregiver
tasks; and (3) it presents a domain independent mobile health conversational
agent for health intervention delivery. We will discuss our approach and
analyze the results of a one month validation study on physical activity,
healthy diet and stress management
Health Figures: An Open Source JavaScript Library for Health Data Visualization
The way we look at data has a great impact on how we can understand it,
particularly when the data is related to health and wellness. Due to the
increased use of self-tracking devices and the ongoing shift towards preventive
medicine, better understanding of our health data is an important part of
improving the general welfare of the citizens. Electronic Health Records,
self-tracking devices and mobile applications provide a rich variety of data
but it often becomes difficult to understand. We implemented the hFigures
library inspired on the hGraph visualization with additional improvements. The
purpose of the library is to provide a visual representation of the evolution
of health measurements in a complete and useful manner. We researched the
usefulness and usability of the library by building an application for health
data visualization in a health coaching program. We performed a user evaluation
with Heuristic Evaluation, Controlled User Testing and Usability
Questionnaires. In the Heuristics Evaluation the average response was 6.3 out
of 7 points and the Cognitive Walkthrough done by usability experts indicated
no design or mismatch errors. In the CSUQ usability test the system obtained an
average score of 6.13 out of 7, and in the ASQ usability test the overall
satisfaction score was 6.64 out of 7. We developed hFigures, an open source
library for visualizing a complete, accurate and normalized graphical
representation of health data. The idea is based on the concept of the hGraph
but it provides additional key features, including a comparison of multiple
health measurements over time. We conducted a usability evaluation of the
library as a key component of an application for health and wellness
monitoring. The results indicate that the data visualization library was
helpful in assisting users in understanding health data and its evolution over
time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016
Healthcare Robotics
Robots have the potential to be a game changer in healthcare: improving
health and well-being, filling care gaps, supporting care givers, and aiding
health care workers. However, before robots are able to be widely deployed, it
is crucial that both the research and industrial communities work together to
establish a strong evidence-base for healthcare robotics, and surmount likely
adoption barriers. This article presents a broad contextualization of robots in
healthcare by identifying key stakeholders, care settings, and tasks; reviewing
recent advances in healthcare robotics; and outlining major challenges and
opportunities to their adoption.Comment: 8 pages, Communications of the ACM, 201
Visions and Challenges in Managing and Preserving Data to Measure Quality of Life
Health-related data analysis plays an important role in self-knowledge,
disease prevention, diagnosis, and quality of life assessment. With the advent
of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices
(wearables, home-medical sensors, etc) facilitates data collection and provide
cloud storage with a central administration. More recently, blockchain and
other distributed ledgers became available as alternative storage options based
on decentralised organisation systems. We bring attention to the human data
bleeding problem and argue that neither centralised nor decentralised system
organisations are a magic bullet for data-driven innovation if individual,
community and societal values are ignored. The motivation for this position
paper is to elaborate on strategies to protect privacy as well as to encourage
data sharing and support open data without requiring a complex access protocol
for researchers. Our main contribution is to outline the design of a
self-regulated Open Health Archive (OHA) system with focus on quality of life
(QoL) data.Comment: DSS 2018: Data-Driven Self-Regulating System
Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour
Health and fitness wearable technology has recently advanced, making it
easier for an individual to monitor their behaviours. Previously self generated
data interacts with the user to motivate positive behaviour change, but issues
arise when relating this to long term mention of wearable devices. Previous
studies within this area are discussed. We also consider a new approach where
data is used to support instead of motivate, through monitoring and logging to
encourage reflection. Based on issues highlighted, we then make recommendations
on the direction in which future work could be most beneficial
Digital Wellness Services: Key to Better Quality of Life for Young Elderly
Digital wellness services for the “young elderly” (the 60-75 years old age group) will be interventions in their daily routines and if/when they are accepted and adopted they will help keep the young elderly in better shape for their senior years (75+). This will contribute to significant reductions in the estimated costs for health and social care for the ageing population. On an individual level, digital wellness services contribute to a better quality of life if designed to fit the needs of the young elderly. Platform tech- nology for digital services offers possible tools for intervention if the tools and services fit the requirements of the young elderly. We summarize several of our studies as a syn- thesis and work out a conceptual framework to facilitate the design and implementation of digital wellness services
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