10,348 research outputs found
360 Quantified Self
Wearable devices with a wide range of sensors have contributed to the rise of
the Quantified Self movement, where individuals log everything ranging from the
number of steps they have taken, to their heart rate, to their sleeping
patterns. Sensors do not, however, typically sense the social and ambient
environment of the users, such as general life style attributes or information
about their social network. This means that the users themselves, and the
medical practitioners, privy to the wearable sensor data, only have a narrow
view of the individual, limited mainly to certain aspects of their physical
condition.
In this paper we describe a number of use cases for how social media can be
used to complement the check-up data and those from sensors to gain a more
holistic view on individuals' health, a perspective we call the 360 Quantified
Self. Health-related information can be obtained from sources as diverse as
food photo sharing, location check-ins, or profile pictures. Additionally,
information from a person's ego network can shed light on the social dimension
of wellbeing which is widely acknowledged to be of utmost importance, even
though they are currently rarely used for medical diagnosis. We articulate a
long-term vision describing the desirable list of technical advances and
variety of data to achieve an integrated system encompassing Electronic Health
Records (EHR), data from wearable devices, alongside information derived from
social media data.Comment: QCRI Technical Repor
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
Performance assessment of a closed-loop system for diabetes management
Telemedicine systems can play an important
role in the management of diabetes, a chronic condition that
is increasing worldwide. Evaluations on the consistency of
information across these systems and on their performance
in a real situation are still missing. This paper presents a
remote monitoring system for diabetes management based
on physiological sensors, mobile technologies and patient/
doctor applications over a service-oriented architecture that
has been evaluated in an international trial (83,905 operation
records). The proposed system integrates three types of
running environments and data engines in a single serviceoriented
architecture. This feature is used to assess key
performance indicators comparing them with other type
of architectures. Data sustainability across the applications
has been evaluated showing better outcomes for full integrated
sensors. At the same time, runtime performance of
clients has been assessed spotting no differences regarding
the operative environmentThe authors wish to acknowledge the consortium of the METABO project (funded by the European Commission, Grant nr. 216270) for their commitment during concept development and trial execution.Martínez Millana, A.; Fico, G.; Fernández Llatas, C.; Traver Salcedo, V. (2015). Performance assessment of a closed-loop system for diabetes management. Medical and Biological Engineering and Computing. 53(12):1295-1303. doi:10.1007/s11517-015-1245-3S129513035312Bellazzi R, Larizza C, Montani A et al (2002) A telemedicine support dor diabetes management: the T-IDDM project. Comput Methods Programs Biomed 69:147–161Boloor K, Chirkova R, Salo T, Viniotis Y (2011) Analysis of response time percentile service level agreements in soa-based applications. IEEE global telecommunications conference (GLOBECOM 2011), dec. 2011, pp 1–6Cartwright M et al (2013) Effect of telehealth on quality of life and psychological outcomes over 12 months: nested study of patient reported outcomes in a pragmatic, cluster randomised controlled trial. BMJ 346:f653Chen I-Y et al (2008) Pervasive digital monitoring and transmission of pre-care patient biostatics with an OSGi, MOM and SOA based remote health care system. In: Proceedings of the 6th annual IEEE international conference on PerCom. Hong KongFico G, Fioravanti A, Arredondo MT, Leuteritz JP, Guillén A, Fernandez D (2011) A user centered design approach for patient interfaces to a diabetes IT platform. Conf Proc IEEE Eng Med Biol Soc 2011:1169–1172Fioravanti A, Fico G, Arredondo MT, Salvi D, Villalar JL (2010) Integration of heterogeneous biomedical sensors into an ISO/IEEE 11073 compliant application. In: Engineering in medicine and biology society (EMBC), 2010 Annual international conference of the IEEE, pp 1049–1052García Saez G et al (2009) Architecture of a wireless personal assistant for telemedical diabetes care. Int J Med Inform 9(78):391–403Gómez EJ, Hernando ME et al (2008) The INCA system: a further step towards a telemedical artificial pancreas. IEEE Trans Inf Technol Biomed 12(4):470–479Harrison’s Principles of Internal Medicine (2011) McGraw-Hill. ISBN:978-0071748896. Ed. July 2011Ke X, Li W et al (2010) WCDMA KPI framework definition methods and applications. ICCET proceedings V4-471–V4-475Klonof D (2013) Twelve modern digital technologies that are transforming decision making for diabetes and all areas of health care. J Diabetes Sci Technol 7(2):291–295Lanzola G et al (2007) Going mobile with a multiaccess service for the management of diabetic patients. J Diabetes Sci Technol 1(5):730–737Ma C et al (2006) Empowering patients with essential information and communication support in the context of diabetes. Int J Med Inform 75(8):577–596Müller AJ, Knuth M, Nikolaus KS, Krivánek R, Küster F, Hasslacher C (2013) First clinical evaluation of a new percutaneous optical fiber glucose sensor for continuous glucose monitoring in diabetes. J Diabetes Sci Technol 7:13Nundy S et al (2012) Using mobile health to support chronic care model: developing an institutional model. Int J Telemed Appl 2012, Art Id 871925. doi: 10.1155/2012/871925Obstfelder A, Engeseth KH, Wynn R (2007) Characteristic of succesfully implemented telemedical applications. Implement Sci 2:25Pravin P et al (2012) A framework for the comparison of mobile patient monitoring systems. J Biomed Inf 45:544–556Reichel A, Rietzsch H, Ludwig B, Röthig K, Moritz A, Bornstein S (2013) Self-adjustment of insulin dose using graphically depicted self-monitoring of blood glucose measurements in patients with type 1 diabetes mellitus. J Diabetes Sci Technol 7(1):156–162Ryan D et al (2012) Clinical and cost effectiveness of mobile phone supported self-monitoring of asthma: multicenter randomized controlled trial. BMJ 344:e1756Schade DS et al (2005) To pump or not to pump. Diabetes Technol Therapeutics 7:845–848Stravroula G, Bartsocas CS et al (2010) SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients. IEEE Trans Inf Technol Biomed 14(3):622–633The Diabetes Control and Complications Trial Research Group (1993) The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 329(14):977–986Trief PM, Morin PC, Izquierdo R, Teresi JA, Eimicke JP, Goland R, Starren J, Shea S, Winstock RS (2006) Depression and glycaemic control in elderly etchnically diverse patients with diabetes: the IDEATel project. Diabetes Care 29(4):830–835van der Weegentres S et al (2013) The development of a mobile monitoring and feedback tool to stimulate physical activity of people with a chronic disease in primary care: a user-centered design. JMIR 1(2):e8Wakefield BJ et al (2014) Effect of home telemonitoring on glycemic and blood pressure control in primary care clinic patients with diabetes. Telemed e-Health 20(3):199–205. doi: 10.1089/tmj.2013.0151Winkler S et al (2011) A new telemonitoring system intended for chronic heart failure patients using mobile technology—Feasibility Study. Int J Cardiol 153:55–58Zhou YY, Kanter MH, Wang JJ, Garrido T (2010) Improved quality at kaiser permanente through e-mail between physicians and patients. Health Aff 29(7):1370–137
mHealth: monitoring platform for diabetes patients
Diabetes is a metabolic disease that can be explained by the high level of glucose in the blood. Constant monitoring of
patients with this type of disease is crucial to the success of their treatment due to the high number of factors that condition it,
such as nutrition, exercise and insulin production. This research consists of a software development project based on mHealth
practice, which aims to cover all the needs of patients and health professionals, introducing improvements in the prevention,
diagnosis and control of endocrine pathology, as well as improvements in hospital management. The web platform should be able
to send a warning to the healthcare professional in cases where a patient's recorded level exceeds normal values and contain all
the patient's records. The aim is to provide support to treatment, monitoring and data collection based on IoT principles, where
medical devices allow communication between machines and interaction between them, sharing and managing data. The
healthcare professional will have the necessary information to assess the health status of his patient and, if necessary, make some
changes to improve the patient's daily routines.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project
Scope: UIDB/00319/2020
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
PREDIRCAM eHealth platform for individualized telemedical assistance for lifestyle modification in the treatment of obesity, diabetes, and cardiometabolic risk prevention: a pilot study (PREDIRCAM 1)
Background:
Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk.
Various international scientific and health organizations have advocated the use of new technologies to solve
these problems. The PREDIRCAM project explores the contribution that a technological system could offer for
the continuous monitoring of lifestyle habits and individualized treatment of obesity as well as cardiometabolic
risk prevention.
Methods:
PREDIRCAM is a technological platform for patients and professionals designed to improve the effectiveness
of lifestyle behavior modifications through the intensive use of the latest information and communication
technologies. The platform consists of a web-based application providing communication interface with
monitoring devices of physiological variables, application for monitoring dietary intake, ad hoc electronic
medical records, different communication channels, and an intelligent notification system. A 2-week feasibility
study was conducted in 15 volunteers to assess the viability of the platform.
Results:
The website received 244 visits (average time/session: 17 min 45 s). A total of 435 dietary intakes were recorded
(average time for each intake registration, 4 min 42 s ± 2 min 30 s), 59 exercises were recorded in 20 heart
rate monitor downloads, 43 topics were discussed through a forum, and 11 of the 15 volunteers expressed a
favorable opinion toward the platform. Food intake recording was reported as the most laborious task. Ten of
the volunteers considered long-term use of the platform to be feasible.
Conclusions:
The PREDIRCAM platform is technically ready for clinical evaluation. Training is required to use the platform
and, in particular, for registration of dietary food intake
Promoting Health for Chronic Conditions: a Novel Approach that integrates Clinical and Personal Decision Support
Direct and indirect economic costs related to chronic diseases are increasing in Europe due to the aging of population. One of the most challenging goals is to improve the quality of life of patients affected by chronic conditions, and enhance their self-management. In this paper, we propose a novel architecture of a scalable solution, based on mobile tools, aimed to keep patients with chronic diseases away from acute episodes, to improve their quality of life and, consequently, to reduce their economic impact. Our solution aims to provide patients with a personalized tool for improving self-management, and it supports both patients and clinicians in decision-making through the implementation of two different Decision Support Systems. Moreover, the proposed architecture takes into account the interoperability and, particularly, the compliance with data transfer protocols (e.g., BT4/LE, ANT+, ISO/IEEE 11073) to ensure integration with existing devices, and with the semantic web approaches and standards related to the content and structure of the information (e.g., HL7, ICD-10 and openEHR) to ensure correct sharing of information with hospital information systems, and classification of patient behaviors (Coelition). The solution will be implemented and validated in future study
Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body
There is a significant increase of strokes, heart diseases and premature death, people need more than ever to be aware of their vital signs such as blood pressure, heart beats, cholesterol level etc. Monitoring and analysing this medical data can help increase the awareness of the risk factor of heart disease. However, there is a huge pressure on medical staff and general practitioners (GPs), therefore this research proposes a medical data analysis based on Nao robots to meet these needs and it will serve as an automated approach towards a robotics real-time interaction with the human body. The proposed research offers a new way to allow users to understand the meaning of their vital signs using a human robot interaction. The developed system has been tested on publicly available data and simulated data. It can predict the future risk of heart disease based on some data attributes. Based on the risk prediction, it can feedback the result and the required lifestyle changes to avoid any related risk
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