| 1. |
- Abtahi, Farhad, et al.
(författare)
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Biosignal PI, an Affordable Open-Source ECG and Respiration Measurement System
- 2014
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 15:1, s. 93-109
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Tidskriftsartikel (refereegranskat)abstract
- Bioimedical pilot projects e.g., telemedicine, homecare, animal and human trials usually involve several physiological measurements. Technical development of these projects is time consuming and in particular costly. A versatile but affordable biosignal measurement platform can help to reduce time and risk while keeping the focus on the important goal and making an efficient use of resources. In this work, an affordable and open source platform for development of physiological signals is proposed. As a first step an 8–12 leads electrocardiogram (ECG) and respiration monitoring system is developed. Chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 for patient safety. The result shows the potential of this platform as a base for prototyping compact, affordable, and medically safe measurement systems. Further work involves both hardware and software development to develop modules. These modules may require development of front-ends for other biosignals or just collect data wirelessly from different devices e.g., blood pressure, weight, bioimpedance spectrum, blood glucose, e.g., through Bluetooth. All design and development documents, files and source codes will be available for non-commercial use through project website, BiosignalPI.org.
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| 2. |
- Abtahi, Farhad, 1981-, et al.
(författare)
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Development and preliminary evaluation of an Android based heart rate variability biofeedback system
- 2014
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Ingår i: Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. - : IEEE. - 9781424479290 ; 2014, s. 3382-5
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Konferensbidrag (refereegranskat)abstract
- The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic electrical bioimpedance (respiration) measurement device has been developed. The system performance and usability have been evaluated in a brief study with eight healthy volunteers. The result demonstrates real-time performance of system and positive effects of biofeedback training session by increased HRV and reduced heart rate. Further development of the application and training protocol is ongoing to investigate duration of training session to find an optimum length and interval of biofeedback sessions to use in potential interventions.
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| 3. |
- Seoane, Fernando, et al.
(författare)
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Mean Expected Error in Prediction of Total Body Water: A True Accuracy Comparison between Bioimpedance Spectroscopy and Single Frequency Regression Equations
- 2015
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Ingår i: Biomed Research International. - : Hindawi Limited. - 2314-6133 .- 2314-6141. ; 2015:Article ID 656323
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Tidskriftsartikel (refereegranskat)abstract
- For several decades electrical bioimpedance (EBI) has been used to assess body fluid distribution and body composition. Despite the development of several different approaches for assessing total body water (TBW), it remains uncertain whether bioimpedance spectroscopic (BIS) approaches are more accurate than single frequency regression equations. The main objective of this study was to answer this question by calculating the expected accuracy of a single measurement for different EBI methods. The results of this study showed that all methods produced similarly high correlation and concordance coefficients, indicating good accuracy as a method. Even the limits of agreement produced from the Bland-Altman analysis indicated that the performance of single frequency, Sun's prediction equations, at population level was close to the performance of both BIS methods; however, when comparing the Mean Absolute Percentage Error value between the single frequency prediction equations and the BIS methods, a significant difference was obtained, indicating slightly better accuracy for the BIS methods. Despite the higher accuracy of BIS methods over 50 kHz prediction equations at both population and individual level, the magnitude of the improvement was small. Such slight improvement in accuracy of BIS methods is suggested insufficient to warrant their clinical use where the most accurate predictions of TBW are required, for example, when assessing over-fluidic status on dialysis. To reach expected errors below 4-5%, novel and individualized approaches must be developed to improve the accuracy of bioimpedance-based methods for the advent of innovative personalized health monitoring applications.
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| 4. |
- Seoane, Fernando, et al.
(författare)
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Slightly superior performance of bioimpedance spectroscopy over single frequency regression equations for assessment of total body water.
- 2015
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Ingår i: Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE. 25-29 Aug. 2015, Milan, Italy.. - : IEEE. - 1094-687X .- 1558-4615. - 9781424492718 - 9781424492701 ; 2015, s. 3707-10
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Konferensbidrag (refereegranskat)abstract
- Electrical bioimpedance has been used for several decades to assess body fluid distribution and body composition by using single frequency and bioimpedance spectroscopic (BIS) techniques. It remains uncertain whether BIS methods have better performance compare to single frequency regression equations. In this work the performance of two BIS methods and four different 50 kHz single frequency prediction equations was studied in a data set of wrist-to-ankle tetrapolar BIS measurements (5-1000 kHz) together with reference values of total body water obtained by tritium dilution in 92 patients. Data were compared using regression techniques and Bland-Altman plots. The results of this study showed that all methods produced similarly high correlation and concordance coefficients, indicating good accuracy as a method. Limits of agreement analysis indicated that the population level performance of Sun's prediction equations was very similar to the performance of both BIS methods. However, BIS methods in practice have slightly better predictive performance than the single-frequency equations as judged by higher correlation and the limits of agreement from the Bland-Altman analysis. In any case, the authors believe that an accurate evaluation of performance of the methods cannot be done as long as the evaluation is done using Bland-Altman analysis, the commonly accepted technique for this kind of performance comparisons.
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| 5. |
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| 6. |
- Abtahi, Farhad, 1981-, et al.
(författare)
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An Affordable ECG and Respiration Monitoring System Based on Raspberry PI and ADAS1000 : First Step towards Homecare Applications
- 2015
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Ingår i: 16th Nordic-Baltic Conference on Biomedical Engineering. - Cham : Springer. - 9783319129662 ; , s. 5-8, s. 5-8
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Konferensbidrag (refereegranskat)abstract
- Homecare is a potential solution for problems associated with an aging population. This may involve several physiological measurements, and hence a flexible but affordable measurement device is needed. In this work, we have designed an ADAS1000-based four-lead electrocardiogram (ECG) and respiration monitoring system. It has been implemented using Raspberry PI as a platform for homecare applications. ADuM chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 and IEC 60950 for patient safety. The result proved the potential of Raspberry PI for the design of a compact, affordable, and medically safe measurement device. Further work involves developing a more flexible software for collecting measurements from different devices (measuring, e.g., blood pressure, weight, impedance spectroscopy, blood glucose) through Bluetooth or user input and integrating them into a cloud-based homecare system.
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| 7. |
- Abtahi, Farhad, 1981-
(författare)
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Aspects of Electrical Bioimpedance Spectrum Estimation
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Electrical bioimpedance spectroscopy (EBIS) has been used to assess the status or composition of various types of tissue, and examples of EBIS include body composition analysis (BCA) and tissue characterisation for skin cancer detection. EBIS is a non-invasive method that has the potential to provide a large amount of information for diagnosis or monitoring purposes, such as the monitoring of pulmonary oedema, i.e., fluid accumulation in the lungs. However, in many cases, systems based on EBIS have not become generally accepted in clinical practice. Possible reasons behind the low acceptance of EBIS could involve inaccurate models; artefacts, such as those from movements; measurement errors; and estimation errors. Previous thoracic EBIS measurements aimed at pulmonary oedema have shown some uncertainties in their results, making it difficult to produce trustworthy monitoring methods. The current research hypothesis was that these uncertainties mostly originate from estimation errors. In particular, time-varying behaviours of the thorax, e.g., respiratory and cardiac activity, can cause estimation errors, which make it tricky to detect the slowly varying behaviour of this system, i.e., pulmonary oedema.The aim of this thesis is to investigate potential sources of estimation error in transthoracic impedance spectroscopy (TIS) for pulmonary oedema detection and to propose methods to prevent or compensate for these errors. This work is mainly focused on two aspects of impedance spectrum estimation: first, the problems associated with the delay between estimations of spectrum samples in the frequency-sweep technique and second, the influence of undersampling (a result of impedance estimation times) when estimating an EBIS spectrum. The delay between frequency sweeps can produce huge errors when analysing EBIS spectra, but its effect decreases with averaging or low-pass filtering, which is a common and simple method for monitoring the time-invariant behaviour of a system. The results show the importance of the undersampling effect as the main estimation error that can cause uncertainty in TIS measurements. The best time for dealing with this error is during the design process, when the system can be designed to avoid this error or with the possibility to compensate for the error during analysis. A case study of monitoring pulmonary oedema is used to assess the effect of these two estimation errors. However, the results can be generalised to any case for identifying the slowly varying behaviour of physiological systems that also display higher frequency variations. Finally, some suggestions for designing an EBIS measurement system and analysis methods to avoid or compensate for these estimation errors are discussed.
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| 8. |
- Abtahi, Farhad, et al.
(författare)
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Association of drivers’ sleepiness with heart rate variability : A pilot study with drivers on real roads
- 2018
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Ingår i: IFMBE Proceedings. - Singapore : Springer Verlag. - 9789811051210 ; , s. 149-152
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Konferensbidrag (refereegranskat)abstract
- Vehicle crashes lead to huge economic and social consequences, and one non-negligible cause of accident is driver sleepiness. Driver sleepiness analysis based on the monitoring of vehicle acceleration, steering and deviation from the road or physiological and behavioral monitoring of the driver, e.g., monitoring of yawning, head pose, eye blinks and eye closures, electroencephalogram, electrooculogram, electromyogram and electrocardiogram (ECG), have been used as a part of sleepiness alert systems.Heart rate variability (HRV) is a potential method for monitoring of driver sleepiness. Despite previous positive reports from the use of HRV for sleepiness detection, results are often inconsistent between studies. In this work, we have re-evaluated the feasibility of using HRV for detecting drivers’ sleepiness during real road driving. A database consists of ECG measurements from 10 drivers, driving during morning, afternoon and night sessions on real road were used. Drivers have reported their average sleepiness level by using the Karolinska sleepiness scale once every five minutes. Statistical analysis was performed to evaluate the potential of HRV indexes to distinguish between alert, first signs of sleepiness and severe sleepiness states. The results suggest that individual subjects show different reactions to sleepiness, which produces an individual change in HRV indicators. The results motivate future work for more personalized approaches in sleepiness detection.
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| 9. |
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| 10. |
- Abtahi, Farhad, 1981-, et al.
(författare)
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Big Data & Wearable Sensors Ensuring Safety and Health @Work
- 2017
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Ingår i: GLOBAL HEALTH 2017, The Sixth International Conference on Global Health Challenges. - 9781612086040
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Konferensbidrag (refereegranskat)abstract
- —Work-related injuries and disorders constitute a major burden and cost for employers, society in general and workers in particular. We@Work is a project that aims to develop an integrated solution for promoting and supporting a safe and healthy working life by combining wearable technologies, Big Data analytics, ergonomics, and information and communication technologies. The We@Work solution aims to support the worker and employer to ensure a healthy working life through pervasive monitoring for early warnings, prompt detection of capacity-loss and accurate risk assessments at workplace as well as self-management of a healthy working life. A multiservice platform will allow unobtrusive data collection at workplaces. Big Data analytics will provide real-time information useful to prevent work injuries and support healthy working life
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