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- Lundell, Sara, 1982-
(författare)
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COPD in primary care : exploring conditions for implementation of evidence-based interventions and eHealth
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Chronic obstructive pulmonary disease (COPD) is a major public health problem. Symptoms and comorbidities associated with COPD affect the whole body. Clinical guidelines for COPD recommend pulmonary rehabilitation (PR) including exercise training and education promoting self-management strategies. Despite the positive effects on health status, few people with COPD have access to PR. Electronic health (eHealth) has been seen as promising for increased access to evidence-based interventions. To increase the likelihood of a successful implementation, it is important to identity enablers and barriers that might affect implementation outcomes. The aim of this thesis is to explore the experiences, interactions and contexts of the management of COPD in primary care, as well as the design, experienced relevance, effect and expected usefulness of eHealth solutions.The thesis is based on four papers that have used qualitative, quantitative and mixed methods. Qualitative interviews (papers I, II, IV) and focus group discussions (paper IV) were analysed using qualitative content analysis (papers I, IV) and grounded theory (paper II). Quantitative data, collected using questionnaires (paper I) and in a systematic review (paper III) was analysed with descriptive statistics (paper I) and meta-analysis (paper III). The qualitative and quantitative findings in paper I and II were merged in a mixed methods design. Participants in the studies included healthcare professionals (papers I, IV), people with COPD (papers II, III, IV), their relatives (paper IV), senior managers representing primary care centres (paper I), and external researchers (paper IV).The findings in this thesis gave insight in the complex interactions within COPD management between the healthcare organisation (e.g. resources and priority), healthcare professionals (e.g. attitudes, collaboration and competence) and people with COPD (e.g. emotions, attitudes and coping). The healthcare organisation is fragmented with few resources and COPD care takes low priority. The healthcare professionals are Building COPD care on shaky ground (paper I), where the shaky ground is a presentation of the non-compliant organisation and other challenging circumstances. Driven, responsible and ambitious healthcare professionals wish to provide empowering COPD interventions through interprofessional collaboration, but are inhibited by their limited knowledge of and experience with COPD. People with COPD are (Re)acting in an ambiguous interaction with primary care providers (paper II), have limited knowledge and struggle with stigma, while they try to accept and manage their disease. The attitudes and support of healthcare professionals’ are essential for necessary interaction and self-management strategies. For people with COPD, this can take different paths: either enhancing confidence with empowering support or coping with disempowering stigma and threat.eHealth solutions such as telehealth, have been used to provide interventions to people with COPD through phone calls, websites or mobile phones, in combination with exercise training and/or education. They show a significant effect on physical activity level, but not on physical capacity and dyspnoea (paper III). Healthcare professionals, people with COPD and their relatives, and external researchers report that, to be useful and relevant in clinical practice, an eHealth tool should be reinforcing existing support structures (paper IV). Furthermore, it needs to fit in the current routines and contexts and create a sense of commitment in its users. According to the participants, information about selfmanagement strategies, such as how-to videos are valuable, and need to help them identify themselves with the people in the videos. The participants regard eHealth as providing knowledge and support for self-management.In conclusion, there is a need for implementation of clinical guidelines for COPD in primary care in order to improve both the management of COPD, as well as the interaction between healthcare professionals and people with COPD. Several actions are needed to facilitate this implementation. The priority and status of COPD management in primary care need to be raised. In addition, more resources (e.g. healthcare professionals) for COPD interventions is required to enhance the conditions for interprofessional collaboration and patient participation. Furthermore, it is important to include physiotherapists in COPD management, considering the focus on exercise training and physical activity. Healthcare professionals in primary care need further training and more time to educate and empower people who have COPD. The use of eHealth may lead to improvements in patient outcomes, although more research on web-based interventions is required. User involvement in the development process of an eHealth tool increases its usefulness and relevance in clinical practice and everyday life. The findings from this thesis may guide implementation processes in primary care, as well as the development of eHealth tools for people with COPD or other long-term conditions.
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| 2. |
- 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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