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1.
J Med Syst ; 42(6): 101, 2018 Apr 17.
Article in English | MEDLINE | ID: mdl-29667028

ABSTRACT

With the rise in wearable technology and "health culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a quick primer on the most commonly monitored physiologic metrics, as well as a brief discussion on the current state of the art in biofeedback-assisted medical applications. We then go on to present a comparative analysis between medical and consumer grade biofeedback devices and discuss the hardware specifications and potential practical applications of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. We end this article with some empirical observations based on our study so that readers might use take them into consideration when arranging a laboratory or real-world experience, thus avoiding costly time delays and material expenditures.


Subject(s)
Biofeedback, Psychology/physiology , Monitoring, Ambulatory/instrumentation , Quality of Life , Remote Sensing Technology/instrumentation , Body Temperature/physiology , Electromyography , Galvanic Skin Response/physiology , Hemodynamics/physiology , Humans , Oximetry , Respiration
2.
J Med Syst ; 41(4): 51, 2017 Apr.
Article in English | MEDLINE | ID: mdl-28214992

ABSTRACT

The Human Immunodeficiency Virus (HIV) is an infectious agent that attacks the immune system cells. Without a strong immune system, the body becomes very susceptible to serious life threatening opportunistic diseases. In spite of the great progresses on medication and prevention over the last years, HIV infection continues to be a major global public health issue, having claimed more than 36 million lives over the last 35 years since the recognition of the disease. Monitoring, through registries, of HIV-AIDS cases is vital to assess general health care needs and to support long-term health-policy control planning. Surveillance systems are therefore established in almost all developed countries. Typically, this is a complex system depending on several stakeholders, such as health care providers, the general population and laboratories, which challenges an efficient and effective reporting of diagnosed cases. One issue that often arises is the administrative delay in reports of diagnosed cases. This paper aims to identify the main factors influencing reporting delays of HIV-AIDS cases within the portuguese surveillance system. The used methodologies included multilayer artificial neural networks (MLP), naive bayesian classifiers (NB), support vector machines (SVM) and the k-nearest neighbor algorithm (KNN). The highest classification accuracy, precision and recall were obtained for MLP and the results suggested homogeneous administrative and clinical practices within the reporting process. Guidelines for reductions of the delays should therefore be developed nationwise and transversally to all stakeholders.


Subject(s)
Algorithms , Data Mining/methods , HIV Infections/diagnosis , HIV Infections/epidemiology , Acquired Immunodeficiency Syndrome/diagnosis , Acquired Immunodeficiency Syndrome/epidemiology , Bayes Theorem , Humans , Neural Networks, Computer , Portugal/epidemiology , Support Vector Machine
3.
J Med Syst ; 41(1): 10, 2017 Jan.
Article in English | MEDLINE | ID: mdl-27864778

ABSTRACT

In recent years Serious Games have evolved substantially, solving problems in diverse areas. In particular, in Cognitive Rehabilitation, Serious Games assume a relevant role. Traditional cognitive therapies are often considered repetitive and discouraging for patients and Serious Games can be used to create more dynamic rehabilitation processes, holding patients' attention throughout the process and motivating them during their road to recovery. This paper reviews Serious Games and user interfaces in rehabilitation area and details a Serious Games platform for Cognitive Rehabilitation that includes a set of features such as: natural and multimodal user interfaces and social features (competition, collaboration, and handicapping) which can contribute to augment the motivation of patients during the rehabilitation process. The web platform was tested with healthy subjects. Results of this preliminary evaluation show the motivation and the interest of the participants by playing the games.


Subject(s)
Cognition Disorders/rehabilitation , Movement , Video Games , Eye Movements , Facial Expression , Humans , Interpersonal Relations , Motivation , Pattern Recognition, Automated/methods , Speech Recognition Software , User-Computer Interface
5.
J Med Syst ; 39(10): 308, 2015 Oct.
Article in English | MEDLINE | ID: mdl-26277614

ABSTRACT

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.


Subject(s)
Algorithms , Data Mining , Decision Support Systems, Clinical , Electronic Health Records/organization & administration , Quality of Life , Adult , Bayes Theorem , Female , Head and Neck Neoplasms/psychology , Health Behavior , Health Status , Humans , Information Systems , Knowledge Management , Male , Middle Aged , Regression Analysis , Smoking/epidemiology , Socioeconomic Factors
6.
Assist Technol ; 25(2): 88-98, 2013.
Article in English | MEDLINE | ID: mdl-23923691

ABSTRACT

This article focuses on evaluating the usability of an intelligent wheelchair (IW) in both real and simulated environments. The wheelchair is controlled at a high-level by a flexible multimodal interface, using voice commands, facial expressions, head movements and joystick as its main inputs. A quasi-experimental design was applied including a deterministic sample with a questionnaire that enabled to apply the system usability scale. The subjects were divided in two independent samples: 46 individuals performing the experiment with an IW in a simulated environment (28 using different commands in a sequential way and 18 with the liberty to choose the command); 12 individuals performing the experiment with a real IW The main conclusion achieved by this study is that the usability of the IW in a real environment is higher than in the simulated environment. However, there were not statistical evidences to affirm that there are differences between the real and simulated wheelchairs in terms of safety and control. Also, most of users considered the multimodal way of driving the wheelchair very practical and satisfactory. Thus, it may be concluded that the multimodal interfaces enables very easy and safe control of the IW both in simulated and real environments.


Subject(s)
Artificial Intelligence , Computer Simulation , Environment Design , Locomotion , User-Computer Interface , Wheelchairs , Adult , Environment, Controlled , Equipment Design , Female , Humans , Male , Patient Satisfaction , Young Adult
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