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- Holtkötter, Jannis, et al.
(författare)
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Development and Validation of a Digital Image Processing-Based Pill Detection Tool for an Oral Medication Self-Monitoring System
- 2022
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 22:8
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Tidskriftsartikel (refereegranskat)abstract
- Long-term adherence to medication is of critical importance for the successful management of chronic diseases. Objective tools to track oral medication adherence are either lacking, expensive, difficult to access, or require additional equipment. To improve medication adherence, cheap and easily accessible objective tools able to track compliance levels are necessary. A tool to monitor pill intake that can be implemented in mobile health solutions without the need for additional devices was developed. We propose a pill intake detection tool that uses digital image processing to analyze images of a blister to detect the presence of pills. The tool uses the Circular Hough Transform as a feature extraction technique and is therefore primarily useful for the detection of pills with a round shape. This pill detection tool is composed of two steps. First, the registration of a full blister and storing of reference values in a local database. Second, the detection and classification of taken and remaining pills in similar blisters, to determine the actual number of untaken pills. In the registration of round pills in full blisters, 100% of pills in gray blisters or blisters with a transparent cover were successfully detected. In the counting of untaken pills in partially opened blisters, 95.2% of remaining and 95.1% of taken pills were detected in gray blisters, while 88.2% of remaining and 80.8% of taken pills were detected in blisters with a transparent cover. The proposed tool provides promising results for the detection of round pills. However, the classification of taken and remaining pills needs to be further improved, in particular for the detection of pills with non-oval shapes.
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- Lee, Jinseok, et al.
(författare)
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Atrial flutter and atrial tachycardia detection using Bayesian approach with high resolution time-frequency spectrum from ECG recordings
- 2013
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Ingår i: Biomedical Signal Processing and Control. - : Elsevier BV. - 1746-8094. ; 8:6, s. 992-999
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Tidskriftsartikel (refereegranskat)abstract
- Contemporary methods of atrial flutter (AFL), atrial tachycardia (AT), and atrial fibrillation (AF) monitoring, although superior to the standard 12-lead ECG and symptom-based monitoring, are unable to accurately discriminate between AF, AFL and AT. Thus, there is a need to develop accurate, automated, and comprehensive atrial arrhythmia detection algorithms using standard ECG recorders. To this end, we have developed a sensitive and real-time realizable algorithm for accurate AFL and AT detection using any standard electrocardiographic recording. Our novel method for automatic detection of atrial flutter and atrial tachycardia uses a Bayesian approach followed by a high resolution time-frequency spectrum. We find the TQ interval of the electrocardiogram (ECG) corresponding to atrial activity by using a particle filter (PF), and analyze the atrial activity with a high resolution time-frequency spectral method: variable frequency complex demodulation (VFCDM). The rationale for using a high-resolution time-frequency algorithm is that our approach tracks the time-varying fundamental frequency of atrial activity, where AT is within 2.0-4.0 Hz, AFL is within 4.0-5.3 Hz and NSR is found at frequencies less than 2.0 Hz. For classifications of AFL (n = 22), AT (n = 10) and normal sinus rhythms (NSR) (n = 29), we found that our approach resulted in accuracies of 0.89, 0.87 and 0.91, respectively; the overall accuracy was 0.88. (C) 2013 Elsevier Ltd. All rights reserved.
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