| 11. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
A Multi-Modal Case-Based System for Clinical Diagnosis and Treatment in Stress Management
- 2009
-
Konferensbidrag (refereegranskat)abstract
- A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often base their diagnosis and decision on manual inspection of signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with the manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. A computer system, classifying the sensor signals is one valuable property assisting a clinician. This paper presents a case-based system that assist a clinician in diagnosis and treatment of stress. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques such as textual information retrieval, rule-based reasoning, and fuzzy logic have been combined together with case-based reasoning to enable more reliable and efficient diagnosis and treatment of stress. The performance has been validated implementing a research prototype and close collaboration with the experts. The experimental results suggest that such a system is valuable both for the less experienced clinicians and for experts where the system may be seen as a second option.
|
|
| 12. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
A Multi-Module Case Based Biofeedback System for Stress Treatment
- 2011
-
Ingår i: Artificial Intelligence in Medicine. - : Elsevier BV. - 0933-3657 .- 1873-2860. ; 51:2, s. 107-115
-
Tidskriftsartikel (refereegranskat)abstract
- Biofeedback is today a recognized treatment method for a number of physical and psychological problems. Experienced clinicians often achieve good results in these areas and their success largely builds on many years of experience and often thousands of treated patients. Unfortunately many of the areas where biofeedback is used are very complex, e.g. diagnosis and treatment of stress. Less experienced clinicians may even have difficulties to initially classify the patient correctly. Often there are only a few experts available to assist less experienced clinicians. To reduce this problem we propose a computer assisted biofeedback system helping in classification, parameter setting and biofeedback training. By adopting a case based approach in a computer-based biofeedback system, decision support can be offered to less experienced clinicians and provide a second opinion to experts. We explore how such a system may be designed and validate the approach in the area of stress where the system assists in the classification, parameter setting and finally in the training. In a case study we show that the case based biofeedback system outperforms novice clinicians based on a case library of cases authorized by an expert.
|
|
| 13. |
- Ahmed, Mobyen Uddin, 1976-
(författare)
-
A Multimodal Approach for Clinical Diagnosis and Treatment
- 2011
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A computer-aided Clinical Decision Support System (CDSS) for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSS could function as an expert for a less experienced clinician or as a second option/opinion of an experienced clinician to their decision making task. Nevertheless, it has been a real challenge to design and develop such a functional system where accuracy of the system performance is an important issue. This research work focuses on development of intelligent CDSS based on a multimodal approach for diagnosis, classification and treatment in medical domains i.e. stress and post-operative pain management domains. Several Artificial Intelligence (AI) techniques such as Case-Based Reasoning (CBR), textual Information Retrieval (IR), Rule-Based Reasoning (RBR), Fuzzy Logic and clustering approaches have been investigated in this thesis work. Patient’s data i.e. their stress and pain related information are collected from complex data sources for instance, finger temperature measurements through sensor signals, pain measurements using a Numerical Visual Analogue Scale (NVAS), patient’s information from text and multiple choice questionnaires. The proposed approach considers multimedia data management to be able to use them in CDSSs for both the domains. The functionalities and performance of the systems have been evaluated based on close collaboration with experts and clinicians of the domains. In stress management, 68 measurements from 46 subjects and 1572 patients’ cases out of ≈4000 in post-operative pain have been used to design, develop and validate the systems. In the stress management domain, besides the 68 measurement cases, three trainees and one senior clinician also have been involved in order to conduct the experimental work. The result from the evaluation shows that the system reaches a level of performance close to the expert and better than the senior and trainee clinicians. Thus, the proposed CDSS could be used as an expert for a less experienced clinician (i.e. trainee) or as a second option/opinion for an experienced clinician (i.e. senior) to their decision making process in stress management. In post-operative pain treatment, the CDSS retrieves and presents most similar cases (e.g. both rare and regular) with their outcomes to assist physicians. Moreover, an automatic approach is presented in order to identify rare cases and 18% of cases from the whole cases library i.e. 276 out of 1572 are identified as rare cases by the approach. Again, among the rare cases (i.e. 276), around 57.25% of the cases are classified as ‘unusually bad’ i.e. the average pain outcome value is greater or equal to 5 on the NVAS scale 0 to 10. Identification of rear cases is an important part of the PAIN OUT project and can be used to improve the quality of individual pain treatment.
|
|
| 14. |
- Ahmed, Mobyen Uddin
(författare)
-
A Personalized Health-Monitoring System for Elderly by Combining Rules and Case-based Reasoning
- 2015
-
Ingår i: Studies in Health Technology and Informatics, Volume 21. ; , s. 249-254
-
Konferensbidrag (refereegranskat)abstract
- Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly’s medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.
|
|
| 15. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
A Three Phase Computer Assisted Biofeedback Training System Using Case-Based Reasoning
- 2008
-
Ingår i: Proc. 9th European Conference on Case-based Reasoning. ; , s. 57-68
-
Konferensbidrag (refereegranskat)abstract
- Biofeedback is a method gaining increased interest and showing good results for a number of physical and psychological problems. Biofeedback training is mostly guided by an experienced clinician and the results largely rely on the clinician's competence. In this paper we propose a three phase computer assisted sensor-based biofeedback decision support system assisting less experienced clinicians, acting as second opinion for experienced clinicians. The three phase CBR framework is deployed to classify a patient, estimate initial parameters and to make recommendations for biofeedback training by retrieving and comparing with previous similar cases in terms of features extracted. The three phases work independently from each other. Moreover, fuzzy techniques are incorporated into our CBR system to better accommodate uncertainty in clinicians reasoning as well as decision analysis. All parts in the proposed framework have been implemented and primarily validated in a prototypical system. The initial result shows how the three phases functioned with CBR technique to assist biofeedback training. Eventually the system enables the clinicians to allow a patient to train himself/herself unsupervised.
|
|
| 16. |
- Ahmed, Mobyen Uddin, Dr, 1976-, et al.
(författare)
-
A vision-based indoor navigation system for individuals with visual impairment
- 2019
-
Ingår i: International Journal of Artificial Intelligence. - : CESER Publications. - 0974-0635. ; 17:2, s. 188-201
-
Tidskriftsartikel (refereegranskat)abstract
- Navigation and orientation in an indoor environment are a challenging task for visually impaired people. This paper proposes a portable vision-based system to provide support for visually impaired persons in their daily activities. Here, machine learning algorithms are used for obstacle avoidance and object recognition. The system is intended to be used independently, easily and comfortably without taking human help. The system assists in obstacle avoidance using cameras and gives voice message feedback by using a pre-trained YOLO Neural Network for object recognition. In other parts of the system, a floor plane estimation algorithm is proposed for obstacle avoidance and fuzzy logic is used to prioritize the detected objects in a frame and generate alert to the user about possible risks. The system is implemented using the Robot Operating System (ROS) for communication on a Nvidia Jetson TX2 with a ZED stereo camera for depth calculations and headphones for user feedback, with the capability to accommodate different setup of hardware components. The parts of the system give varying results when evaluated and thus in future a large-scale evaluation is needed to implement the system and get it as a commercialized product in this area.
|
|
| 17. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
-
A case-based patient identification system using pulseoximeter and a personalized health profile
- 2012
-
Ingår i: Proceedings of the ICCBR 2012 Workshops. - Lyon, France. ; , s. 117-128
-
Konferensbidrag (refereegranskat)abstract
- This paper proposes a case-based system framework in order to identify patient using their health parameters taken with physiological sensors. It combines a personalized health profiling protocol with a Case-Based Reasoning (CBR) approach. The personalized health profiling helps to determine a number of individual parameters which are important inputs for a clinician to make the final diagnosis and treatment plan. The proposed system uses a pulse oximeter that measures pulse rate and blood oxygen saturation. The measurements are taken through an android application in a smart phone which is connected with the pulseoximeter and bluetooth communication. The CBR approach helps clinicians to make a diagnosis, classification and treatment plan by retrieving the most similar previous case. The case may also be used to follow the treatment progress. Here, the cases are formulated with person’s contextual information and extracted features from sensor signal measurements. The features are extracted considering three domain analysis:1) time domain features using statistical measurement, 2) frequency domain features applying Fast Fourier Transform (FFT), and 3) time-frequency domain features applying Discrete Wavelet Transform (DWT). The initial result is acceptable that shows the advancement of the system while combining the personalized health profiling together with CBR.
|
|
| 18. |
- Ahmed, Mobyen Uddin, 1976-
(författare)
-
An Intelligent Healthcare Service to Monitor Vital Signs in Daily Life – A Case Study on Health-IoT
- 2017
-
Ingår i: International Journal of Engineering Research and Applications. - Sweden : IOSR Journals. - 2248-9622. ; 7:3, s. 43-55
-
Tidskriftsartikel (refereegranskat)abstract
- Vital signs monitoring for elderly in daily life environment is a promising concept that efficiently can provide medical services to people at home. However, make the system self-served and functioning as personalized provision makes the challenge even larger. This paper presents a case study on a Health-IoT system where an intelligent healthcare service is developed to monitor vital signs in daily life. Here, a generic Health-IoT framework with a Clinical Decision Support System (CDSS) is presented. The generic framework is mainly focused on the supporting sensors, communication media, secure and safe data communication, cloud-based storage, and remote accesses of the data. The CDSS is used to provide a personalized report on persons’ health condition based on daily basis observation on vital signs. Six participants, from Spain (n=3) and Slovenia (n=3) have been using the proposed healthcare system for eight weeks (e.g. 300+ health measurements) in their home environments to monitor their health. The sensitivity, specificity and overall accuracy of the DSS’s classification are achieved as 90%, 97% and 96% respectively while k=2 i.e., top 2 most similar retrieved cases are considered. The initial user evaluation result demonstrates the feasibility and performance of the implemented system through the proposed framework.
|
|
| 19. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
An Overview of three Medical Applications Using Hybrid Case-Based Reasoning
- 2012
-
Konferensbidrag (refereegranskat)abstract
- Today more and more patient journals are stored electronically but they are rarely used for more than statistical purpose. In this paper we present an approach where clinical patient journals are used for improved clinical decision making on an individual level. The underlying assumption is that medical staff benefit from comparing a specific patient with similar patient. By comparing symptoms, diagnosis, medication and outcome in an individual level they are able to make more informed decisions at the point of care. This paper presents some parts of our more than ten years research efforts in the area and some of the projects and their underlying hybrid approaches. As a foundation for all our projects we use case-based reasoning (CBR) research in combination with techniques from artificial intelligence, data mining, statistics and search techniques. Three systems are presented in two medical domains 1) decision support for stress diagnosis 2) decision support for stress treatment and 3) decision support for post-operative pain treatment and discuss results and lessons learned.
|
|
| 20. |
- Ahmed, Mobyen Uddin, et al.
(författare)
-
An Overview on the Internet of Things for Health Monitoring Systems
- 2016
-
Ingår i: 2nd EAI International Conference on IoT Technologies for HealthCare HealthyIoT2015. - Cham : Springer International Publishing. ; , s. 429-436
-
Konferensbidrag (refereegranskat)abstract
- The aging population and the increasing healthcare cost in hospitals are spurring the advent of remote health monitoring systems. Advances in physiological sensing devices and the emergence of reliable low-power wireless network technologies have enabled the design of remote health monitoring systems. The next generation Internet, commonly referred to as Internet of Things (IoT), depicts a world populated by devices that are able to sense, process and react via the Internet. Thus, we envision health monitoring systems that support Internet connection and use this connectivity to enable better and more reliable services. This paper presents an overview on existing health monitoring systems, considering the IoT vision. We focus on recent trends and the development of health monitoring systems in terms of: (1) health parameters, (2) frameworks, (3) wireless communication, and (4) security issues. We also identify the main limitations, requirements and advantages within these systems.
|
|
