| 1. |
- Abbaspour, Sara, 1984-
(författare)
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Proposing Combined Approaches to Remove ECG Artifacts from Surface EMG Signals
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Electromyography (EMG) is a tool routinely used for a variety of applications in a very large breadth of disciplines. However, this signal is inevitably contaminated by various artifacts originated from different sources. Electrical activity of heart muscles, electrocardiogram (ECG), is one of sources which affects the EMG signals due to the proximity of the collection sites to the heart and makes its analysis non-reliable. Different methods have been proposed to remove ECG artifacts from surface EMG signals; however, in spite of numerous attempts to eliminate or reduce this artifact, the problem of accurate and effective de-noising of EMG still remains a challenge. In this study common methods such as high pass filter (HPF), gating method, spike clipping, hybrid technique, template subtraction, independent component analysis (ICA), wavelet transform, wavelet-ICA, artificial neural network (ANN), and adaptive noise canceller (ANC) and adaptive neuro-fuzzy inference system (ANFIS) are used to remove ECG artifacts from surface EMG signals and their accuracy and effectiveness is investigated. HPF, gating method and spike clipping are fast; however they remove useful information from EMG signals. Hybrid technique and ANC are time consuming. Template subtraction requires predetermined QRS pattern. Using wavelet transform some artifacts remain in the original signal and part of the desired signal is removed. ICA requires multi-channel signals. Wavelet-ICA approach does not require multi-channel signals; however, it is user-dependent. ANN and ANFIS have good performance, but it is possible to improve their results by combining them with other techniques. For some applications of EMG signals such as rehabilitation, motion control and motion prediction, the quality of EMG signals is very important. Furthermore, the artifact removal methods need to be online and automatic. Hence, efficient methods such as ANN-wavelet, adaptive subtraction and automated wavelet-ICA are proposed to effectively eliminate ECG artifacts from surface EMG signals. To compare the results of the investigated methods and the proposed methods in this study, clean EMG signals from biceps and deltoid muscles and ECG artifacts from pectoralis major muscle are recorded from five healthy subjects to create 10 channels of contaminated EMG signals by adding the recorded ECG artifacts to the clean EMG signals. The artifact removal methods are also applied to the 10 channels of real contaminated EMG signals from pectoralis major muscle of the left side. Evaluation criteria such as signal to noise ratio, relative error, correlation coefficient, elapsed time and power spectrum density are used to evaluate the performance of the proposed methods. It is found that the performance of the proposed ANN-wavelet method is superior to the other methods with a signal to noise ratio, relative error and correlation coefficient of 15.53, 0.01 and 0.98 respectively.
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| 2. |
- Andersson, Urban, et al.
(författare)
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Nurses’ experiences of informal coercion on adult psychiatric wards
- 2020
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Ingår i: Nursing Ethics. - : SAGE Publications. - 0969-7330 .- 1477-0989. ; 27:3, s. 741-753
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Tidskriftsartikel (refereegranskat)abstract
- Background:Informal coercion, that is, situations where caregivers use subtle coercive measures to impose their will on patients, is common in adult psychiatric inpatient care. It has been described as ‘a necessary evil’, confronting nurses with an ethical dilemma where they need to balance between a wish to do good, and the risk of violating patients’ dignity and autonomy.Aim:To describe nurses’ experiences of being involved in informal coercion in adult psychiatric inpatient care.Research design:The study has a qualitative, inductive design.Participants and research context:Semi-structured interviews with 10 Swedish psychiatric nurses were analysed with qualitative content analysis.Ethical considerations:The study was performed in accordance with the Declaration of Helsinki. In line with the Swedish Ethical Review Act, it was also subject to ethical procedures at the university.Findings:Four domains comprise informal coercion as a process over time. These domains contain 11 categories focusing on different experiences involved in the process: Striving to connect, involving others, adjusting to the caring culture, dealing with laws, justifying coercion, waiting for the patient, persuading the patient, negotiating with the patient, using professional power, scrutinizing one’s actions and learning together.Discussion:Informal coercion is associated with moral stress as nurses might find themselves torn between a wish to do good for the patient, general practices and ‘house rules’ in the caring culture. In addition, nurses need to be aware of the asymmetry of the caring relationship, in order to avoid compliance becoming a consequence of patients subordinating to nurse power, rather than a result of mutual understanding. Reflections are thus necessary through the process to promote mutual learning and to avoid violations of patients’ dignity and autonomy.Conclusion:If there is a need for coercion, that is, if the coercion is found to be an ‘unpleasant good’, rather than ‘necessary evil’ considering the consequences for the patient, it should be subject to reflecting and learning together with the patient
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| 3. |
- Rattfält, Linda, 1979-, et al.
(författare)
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A Canonical correlation approach to heart beat detection in textile ECG measurements
- 2006
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Ingår i: IET 3rd International Conference On Advances in Medical, Signal and Information Processing, 2006. MEDSIP 2006. - : IEEE. - 0863416586 - 9780863416583 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Research in textile sensors has lead to new ways to measure electrocardiograms (ECG). However, additional disturbances from e.g. muscular noise and high skin-electrode impedances often result in poor signal quality. The paper contains a simple application of canonical correlation analysis (CCA) on multi channel ECG signals recorded with textile electrodes. Using CCA to solve the blind source separation (BSS) problem, we intend to separate the ECG signal from the various noise sources. The method (CCABSS) was compared to simple averaging of the ECG channels and to the independent component analysis method (ICA). A heart beat detector was used to evaluate the signal quality. Results show that the signal was completely lost while simulating various noise in 33%, 17% and 7% of the cases for averaging, ICA and CCA, respectively.
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