| 1. |
- Afifi, S., et al.
(författare)
-
A Novel Medical Device for Early Detection of Melanoma
- 2019
-
Ingår i: Studies in Health Technology and Informatics. - : NLM (Medline). - 0926-9630 .- 1879-8365. ; 261, s. 122-127
-
Tidskriftsartikel (refereegranskat)abstract
- Melanoma is the deadliest form of skin cancer. Early detection of melanoma is vital, as it helps in decreasing the death rate as well as treatment costs. Dermatologists are using image-based diagnostic tools to assist them in decision-making and detecting melanoma at an early stage. We aim to develop a novel handheld medical scanning device dedicated to early detection of melanoma at the primary healthcare with low cost and high performance. However, developing this particular device is very challenging due to the complicated computations required by the embedded diagnosis system. In this paper, we propose a hardware-friendly design for implementing an embedded system by exploiting the recent hardware advances in reconfigurable computing. The developed embedded system achieved optimized implementation results for the hardware resource utilization, power consumption, detection speed and processing time with high classification accuracy rate using real data for melanoma detection. Consequently, the proposed embedded diagnosis system meets the critical embedded systems constraints, which is capable for integration towards a cost- and energy-efficient medical device for early detection of melanoma.
|
|
| 2. |
- Ask, Per, et al.
(författare)
-
NovaMedTech - A regional program for supporting new medical technologies in personalized health care
- 2012
-
Ingår i: Studies in Health Technology and Informatics. - 9781614990680 ; 177, s. 71-5
-
Konferensbidrag (refereegranskat)abstract
- NovaMedTech is an initiative funded from EU structural funds for supporting new medical technologies for personalized health care. It aims at bringing these technologies into clinical use and to the health care market. The program has participants from health care, industry and academia in East middle Sweden. The first three year period of the program was successful in terms of product concepts tried clinically, and number of products brought to a commercialization phase. Further, the program has led to a large number of scientific publications. Among projects supported, we can mention: Intelligent sensor networks; A digital pen to collect medical information about health status from patients; A web-based intelligent stethoscope; Methodologies to measure local blood flow and nutrition using optical techniques; Blood flow assessment from ankle pressure measurements; Technologies for pressure ulcer prevention; An IR thermometer for improved accuracy; A technique that identifies individuals prone to commit suicide among depressed patients; Detection of infectious disease using an electronic nose; Identification of the lactate threshold from breath; Obesity measurements using special software and MR camera; and An optical probe guided tumor resection. During the present three years period emphasis will be on entrepreneurial activities supporting the commercialization and bringing products to the market.
|
|
| 3. |
- Barua, Shaibal, et al.
(författare)
-
Classifying drivers' cognitive load using EEG signals
- 2017
-
Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. - 9781614997603 ; 237, s. 99-106
-
Tidskriftsartikel (refereegranskat)abstract
- A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.
|
|
| 4. |
- Ghareh Baghi, Arash, et al.
(författare)
-
An Edge Computing Method for Extracting Pathological Information from Phonocardiogram
- 2019
-
Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. - 9781614999867 ; 262, s. 364-367
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a structure of decision support system for pediatric cardiac disease, based on an Internet of Things (IoT) framework. The structure performs the intelligent decision making at its edge processing level, which classifies the heart sound signal, to three classes of cardiac conditions, normal, mild disease, and critical disease. Three types of the errors are introduced to evaluate the performance of the processing method, Type 1, 2 and 3, defined as the incorrect classification from the critical disease, mild, and normal, respectively. The method is validated using 140 real data patient records collected from the hospital referrals. The estimated negative errors for the Type 1, and 2, are calculated to be 0% and 4.8%, against the positive errors which are 6.3% and 13.3%, respectively. The Type 3, is calculated to be 16.7%, showing a high sensitivity of the method to be used in an IoT healthcare framework.
|
|
| 5. |
- Ghareh Baghi, Arash, et al.
(författare)
-
Structural Risk Evaluation of a Deep Neural Network and a Markov Model in Extracting Medical Information from Phonocardiography
- 2018
-
Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. - 9781614998792 - 9781614998808 ; 251, s. 157-160
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a method for exploring structural risk of any artificial intelligence-based method in bioinformatics, the A-Test method. This method provides a way to not only quantitate the structural risk associated with a classification method, but provides a graphical representation to compare the learning capacity of different classification methods. Two different methods, Deep Time Growing Neural Network (DTGNN) and Hidden Markov Model (HMM), are selected as two classification methods for comparison. Time series of heart sound signals are employed as the case study where the classifiers are trained to learn the disease-related changes. Results showed that the DTGNN offers a superior performance both in terms of the capacity and the structural risk. The A-Test method can be especially employed in comparing the learning methods with small data size.
|
|
| 6. |
- Gharehbaghi, Arash, et al.
(författare)
-
A Decision Support System for Cardiac Disease Diagnosis Based on Machine Learning Methods
- 2017
-
Ingår i: Studies in Health Technology and Informatics. - : IOS Press. - 0926-9630 .- 1879-8365. - 9781614997528 ; 235, s. 43-47
-
Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a decision support system for screening pediatric cardiac disease in primary healthcare centres relying on the heart sound time series analysis. The proposed system employs our processing method which is based on the hidden Markov model for extracting appropriate information from the time series. The binary output resulting from the method is discriminative for the two classes of time series existing in our databank, corresponding to the children with heart disease and the healthy ones. A total 90 children referrals to a university hospital, constituting of 55 healthy and 35 children with congenital heart disease, were enrolled into the study after obtaining the informed consent. Accuracy and sensitivity of the method was estimated to be 86.4% and 85.6%, respectively, showing a superior performance than what a paediatric cardiologist could achieve performing auscultation. The method can be easily implemented using mobile and web technology to develop an easy-To-use tool for paediatric cardiac disease diagnosis. © 2017 European Federation for Medical Informatics (EFMI) and IOS Press.
|
|
| 7. |
- Gharehbaghi, Arash, et al.
(författare)
-
Distinguishing Septal Heart Defects from the Valvular Regurgitation Using Intelligent Phonocardiography
- 2020
-
Ingår i: Digital Personalized Health and Medicine. - : IOS Press. - 9781643680828 - 9781643680835 ; 270, s. 178-182
-
Konferensbidrag (refereegranskat)abstract
- This paper presents an original machine learning method for extracting diagnostic medical information from heart sound recordings. The method is proposed to be integrated with an intelligent phonocardiography in order to enhance diagnostic value of this technology. The method is tailored to diagnose children with heart septal defects, the pathological condition which can bring irreversible and sometimes fatal consequences to the children. The study includes 115 children referrals to an university hospital, consisting of 6 groups of the individuals: atrial septal defects (10), healthy children with innocent murmur (25), healthy children without any murmur (25), mitral regurgitation (15), tricuspid regurgitation (15), and ventricular septal defect (25). The method is trained to detect the atrial or ventricular septal defects versus the rest of the groups. Accuracy/sensitivity and the structural risk of the method is estimated to be 91.6%/88.4% and 9.89%, using the repeated random sub sampling and the A-Test method, respectively.
|
|
| 8. |
- GholamHosseini, Hamid, et al.
(författare)
-
Obesity Risk Assessment Model Using Wearable Technology with Personalized Activity, Calorie Expenditure and Health Profile
- 2019
-
Ingår i: Studies in Health Technology and Informatics. - : NLM (Medline). - 0926-9630 .- 1879-8365. ; 261, s. 91-96
-
Tidskriftsartikel (refereegranskat)abstract
- There is a worldwide increase in the rate of obesity and its related long-term conditions, emphasizing an immediate need to address this modern-age global epidemic of healthy living. Moreover, healthcare spending on long-term or chronic care conditions such as obesity is increasing to the point that requires effective interventions and advancements to reduce the burden of the healthcare. This research focuses on the early risk assessment of overweight/obesity using wearable technology. We establish an individualised health profile that identifies the level of activity and current health status of an individual using real-time activity and vital signs. We developed an algorithm to assess the risk of obesity using the individual's current activity and calorie expenditure. The algorithm was deployed on a smartphone application to collect wearable device data, and user reported data. Based on the collected data, the proposed application assesses the risk of obesity/overweight, measures the current activity level and recommends an optimized calorie plan.
|
|
| 9. |
- Hagblad, Jimmie, et al.
(författare)
-
Long term monitoring of blood flow at multiple depths - observations of changes.
- 2012
-
Ingår i: Studies in Health Technology and Informatics. - 0926-9630 .- 1879-8365. ; 177, s. 107-112
-
Tidskriftsartikel (refereegranskat)abstract
- Detecting reduced circulation, which is a major factor in the development of pressure ulcers, can be done using optical methods. PPG and LDF can be combined and used to evaluate blood flow at different depths. In this study the use of a probe combining PPG and LDF to monitor multiple tissue depths is evaluated. The effects on blood flow and temperature without additional provocation was examined. Measurements were performed during 60 min and the use of an active probe was compared with the use of a semi-active probe turned off a major part of the time. Changes in temperature and blood flow using these probe configurations (active and semi-active probe) are compared; four different 5 min segments during a 60 min measurement. A general increase in both temperature and blood flow is found but this increase could not be concluded to occur due to the light sources of the probe.
|
|
| 10. |
- Hollmark, Malin, 1975-, et al.
(författare)
-
Technology Ready to be Launched, but is there a Payer? : Challenges for Implementing eHealth in Sweden
- 2015
-
Ingår i: Studies in Health Technology and Informatics. - 0926-9630 .- 1879-8365. ; 211, s. 57-68
-
Tidskriftsartikel (refereegranskat)abstract
- The development of a sustainable, high-quality, affordable health care is today a high priority for many actors in the society. This is to ensure that we will continue to afford to care for the growing portion of elderly in our population. One solution is to enable the individual's power over her own health or illness, and participation in her own care. There are evidently opportunities with the rapid development of eHealth and wearable sensors. Tracking and measuring vital data can help to keep people out of the hospital. Loads of data is generated to help us understand disease, to provide us with early diagnostics and warnings. It is providing us with possibilities to collect and capture the true health status of individuals. Successful technologies demonstrate savings, acceptance among users and improved access to healthcare. But there are also challenges. Implementing new technologies in health care is difficult. Researchers from around the world are reporting on similar problems, such as reimbursement, interoperability, usability and regulatory issues. This paper will discuss a few of these implementation challenges as well as a few of the efforts in meeting them. To conclude, eHealth solutions can contribute to patient empowerment and a sustainable health care. Our assumption is however, that as long as we do not face the implementation challenges and invest in overcoming the pressing obstacles, society will not be able, or willing, to pay for the solutions.
|
|
