Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227629
F. Sun, Weili Chen, Hojeong Yu, Akid Omob, Ryan Brisbin, A. Ganguli, V. Vemuri, P. Strzeboński, Guangzhe Cui, K. J. Allen, Smit Desai, Weiran Lin, David M. Nash, D. Hirschberg, Ian Brooks, R. Bashir, B. Cunningham
New tools are needed to enable rapid detection, identification, and reporting of infectious viral and microbial pathogens in a wide variety of point-of-care applications that impact human and animal health. We report the design, construction, and characterization of a platform for multiplexed analysis of disease-specific DNA sequences that utilizes a smartphone camera as the sensor in conjunction with a handheld instrument that interfaces the phone with a silicon-based microfluidic chip. Utilizing specific nucleic acid sequences for four equine respiratory pathogens as representative examples, we demonstrated the ability of the system to use a single 15-μL droplet of test sample to perform selective positive/negative determination of target sequences, including integrated experimental controls, in approximately 30 minutes. The system achieves detection limits comparable to those obtained by laboratory-based methods and instruments.
{"title":"Multiplexed detection of infectious diseases with microfluidic loop-mediated isothermal amplification and a smartphone","authors":"F. Sun, Weili Chen, Hojeong Yu, Akid Omob, Ryan Brisbin, A. Ganguli, V. Vemuri, P. Strzeboński, Guangzhe Cui, K. J. Allen, Smit Desai, Weiran Lin, David M. Nash, D. Hirschberg, Ian Brooks, R. Bashir, B. Cunningham","doi":"10.1109/HIC.2017.8227629","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227629","url":null,"abstract":"New tools are needed to enable rapid detection, identification, and reporting of infectious viral and microbial pathogens in a wide variety of point-of-care applications that impact human and animal health. We report the design, construction, and characterization of a platform for multiplexed analysis of disease-specific DNA sequences that utilizes a smartphone camera as the sensor in conjunction with a handheld instrument that interfaces the phone with a silicon-based microfluidic chip. Utilizing specific nucleic acid sequences for four equine respiratory pathogens as representative examples, we demonstrated the ability of the system to use a single 15-μL droplet of test sample to perform selective positive/negative determination of target sequences, including integrated experimental controls, in approximately 30 minutes. The system achieves detection limits comparable to those obtained by laboratory-based methods and instruments.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127694822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227597
T. T. Munia, Intisar Rizwan i Haque, A. Aymond, N. Mackinnon, D. Farkas, Minhal Al-Hashim, F. Vasefi, R. Fazel-Rezai
Psoriasis is one of the most stressful skin diseases. The accurate assessment and effective management of the disease is one of the contributing factors in reducing the time required for relieving the disease symptoms. As the treatment is unusually subjective, an automatic and efficient computer aided assessment technique is an active area of research. In this study, we developed an automatic psoriasis segmentation and plaque localization system using images captured by a digital camera. Our work differs from other studies by improving the segmentation of lesion regions and using a novel region based color feature extractor for classification of psoriasis plaques from healthy skin areas. The proposed modified k-means clustering based segmentation approach resulted in an accuracy of 93.83% in comparison to the ground truth, which is around 10% more than reported results by others with the same database. Statistical analysis was performed to determine psoriasis biomarkers, and the effectiveness of these biomarkers was validated by developing a machine learning model consisting of support vector machine (SVM) classifier to identify the psoriasis plaques automatically. The classification model predicted the disease plaques with an acceptable accuracy of 86.83% and thus the automated psoriasis segmentation and plaque localization technique developed in this study provide the foundation towards designing an objective assessment system for psoriasis.
{"title":"Automatic clustering-based segmentation and plaque localization in psoriasis digital images","authors":"T. T. Munia, Intisar Rizwan i Haque, A. Aymond, N. Mackinnon, D. Farkas, Minhal Al-Hashim, F. Vasefi, R. Fazel-Rezai","doi":"10.1109/HIC.2017.8227597","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227597","url":null,"abstract":"Psoriasis is one of the most stressful skin diseases. The accurate assessment and effective management of the disease is one of the contributing factors in reducing the time required for relieving the disease symptoms. As the treatment is unusually subjective, an automatic and efficient computer aided assessment technique is an active area of research. In this study, we developed an automatic psoriasis segmentation and plaque localization system using images captured by a digital camera. Our work differs from other studies by improving the segmentation of lesion regions and using a novel region based color feature extractor for classification of psoriasis plaques from healthy skin areas. The proposed modified k-means clustering based segmentation approach resulted in an accuracy of 93.83% in comparison to the ground truth, which is around 10% more than reported results by others with the same database. Statistical analysis was performed to determine psoriasis biomarkers, and the effectiveness of these biomarkers was validated by developing a machine learning model consisting of support vector machine (SVM) classifier to identify the psoriasis plaques automatically. The classification model predicted the disease plaques with an acceptable accuracy of 86.83% and thus the automated psoriasis segmentation and plaque localization technique developed in this study provide the foundation towards designing an objective assessment system for psoriasis.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125074734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227627
Sakura Sikander, Pradipta Biswas, Pankaj Kulkami, H. Mansy, N. Rahnavard, Sang-Eun Song
Physicians are not evenly distributed throughout the United States. To overcome this physical limitation, we propose a concept of medical expertise pooling, which will redistribute the expertise throughout the nation more evenly. To establish this concept, we are proposing a system with emerging tele sensing and manipulation technologies over the network. In case of emergency, the proposed system can particularly be more important as it will provide more efficient support in the critical battle against time for diagnosis and treatment of a patient. Despite the physical constraint of long distance between the physician and the patient, the system will provide the visual, body sound and tactile feedback to ensure timely diagnosis and treatment that can contribute to increase in survival rates. While the proposed system utilizes existing technologies and resources, it is highly innovative as it implements a medical expert pooling paradigm that can lead to significant advancements in patient care.
{"title":"A concept of medical expertise pooling by tele sensing and manipulation: Emergency medicine case","authors":"Sakura Sikander, Pradipta Biswas, Pankaj Kulkami, H. Mansy, N. Rahnavard, Sang-Eun Song","doi":"10.1109/HIC.2017.8227627","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227627","url":null,"abstract":"Physicians are not evenly distributed throughout the United States. To overcome this physical limitation, we propose a concept of medical expertise pooling, which will redistribute the expertise throughout the nation more evenly. To establish this concept, we are proposing a system with emerging tele sensing and manipulation technologies over the network. In case of emergency, the proposed system can particularly be more important as it will provide more efficient support in the critical battle against time for diagnosis and treatment of a patient. Despite the physical constraint of long distance between the physician and the patient, the system will provide the visual, body sound and tactile feedback to ensure timely diagnosis and treatment that can contribute to increase in survival rates. While the proposed system utilizes existing technologies and resources, it is highly innovative as it implements a medical expert pooling paradigm that can lead to significant advancements in patient care.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131594922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227590
R. E. Smith, Ben Smith, Nathan Borgfeld
Healthcare-associated infections, specifically those acquired as the result of an invasive medical or surgical procedure, are common in first-world nations as well as the developing world, and are associated with high morbidity, mortality, and billions of dollars (US) in cost. Blue light centered at 405 nm has been identified as a potential adjunct antimicrobial tool to treat and prevent infection. An antimicrobial light device has been developed to disinfect skin and wound surfaces by adjusting light intensity and treatment times to provide precise irradiance and fluence values which match effective published values from the literature.
{"title":"An antimicrobial light device with clinical utility in the United States and abroad","authors":"R. E. Smith, Ben Smith, Nathan Borgfeld","doi":"10.1109/HIC.2017.8227590","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227590","url":null,"abstract":"Healthcare-associated infections, specifically those acquired as the result of an invasive medical or surgical procedure, are common in first-world nations as well as the developing world, and are associated with high morbidity, mortality, and billions of dollars (US) in cost. Blue light centered at 405 nm has been identified as a potential adjunct antimicrobial tool to treat and prevent infection. An antimicrobial light device has been developed to disinfect skin and wound surfaces by adjusting light intensity and treatment times to provide precise irradiance and fluence values which match effective published values from the literature.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129728097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227617
Shivanthan A. C. Yohanandan, Chathura Perera, Mary Jones, R. Peppard, T. Perera
Tremor is an involuntary rhythmic muscle movement assessed subjectively by specialists. To improve accuracy and mitigate bias, tremor must be video recorded and rated by multiple experts. Existing video-based motion tracking techniques can be applied to quantify tremor assessment; though, such methods rely on sophisticated and expensive instrumentation as well as specialized skin markers. This paper describes a low-cost markerless method using accessible hardware and open-source software. In a cohort of 8 subjects with tremor undergoing deep brain stimulation therapy, we show our video-based technique has strong concordance (r = 0.93, p < 0.001) with expert tremor ratings. This makes it suitable for point-of-care assessment as well as use in future structured clinical trials.
震颤是一种由专家主观评估的不自主节律性肌肉运动。为了提高准确性和减少偏差，必须对震颤进行视频记录，并由多位专家进行评级。现有的基于视频的运动跟踪技术可用于量化震颤评估;然而，这种方法依赖于复杂而昂贵的仪器以及专门的皮肤标记。本文介绍了一种使用可访问硬件和开源软件的低成本无标记方法。在8名接受深部脑刺激治疗的震颤患者队列中，我们发现基于视频的技术与专家震颤评分有很强的一致性(r = 0.93, p < 0.001)。这使得它适用于即时护理评估以及在未来的结构化临床试验中使用。
{"title":"Objective video-based tremor assessment for movement disorders using open-source software","authors":"Shivanthan A. C. Yohanandan, Chathura Perera, Mary Jones, R. Peppard, T. Perera","doi":"10.1109/HIC.2017.8227617","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227617","url":null,"abstract":"Tremor is an involuntary rhythmic muscle movement assessed subjectively by specialists. To improve accuracy and mitigate bias, tremor must be video recorded and rated by multiple experts. Existing video-based motion tracking techniques can be applied to quantify tremor assessment; though, such methods rely on sophisticated and expensive instrumentation as well as specialized skin markers. This paper describes a low-cost markerless method using accessible hardware and open-source software. In a cohort of 8 subjects with tremor undergoing deep brain stimulation therapy, we show our video-based technique has strong concordance (r = 0.93, p < 0.001) with expert tremor ratings. This makes it suitable for point-of-care assessment as well as use in future structured clinical trials.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125391138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227582
D. S. Wickramasuriya, R. Faghih
Emotional states involving anger, hostility, anxiety and stress have been associated with an increased risk of cardiovascular disease. Online emotion recognition has achieved little attention in the literature in comparison to offline approaches. We present both online and offline methods to identify anger based on EMG data. In the offline method, the Hilbert-Huang transform is used to extract energy features from different time-frequency blocks. This approach achieves an overall classification accuracy of 87.5%. We also develop a novel online method combining machine learning with the tracking of a single parameter for anger detection. Here, band energy is calculated within time windows, and is continuously adjusted based on classified peak amplitudes. Although this technique has a lower classification accuracy than the offline method, it is quite promising as it is well-suited for wearable monitoring and long-term stress management.
{"title":"Online and offline anger detection via electromyography analysis","authors":"D. S. Wickramasuriya, R. Faghih","doi":"10.1109/HIC.2017.8227582","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227582","url":null,"abstract":"Emotional states involving anger, hostility, anxiety and stress have been associated with an increased risk of cardiovascular disease. Online emotion recognition has achieved little attention in the literature in comparison to offline approaches. We present both online and offline methods to identify anger based on EMG data. In the offline method, the Hilbert-Huang transform is used to extract energy features from different time-frequency blocks. This approach achieves an overall classification accuracy of 87.5%. We also develop a novel online method combining machine learning with the tracking of a single parameter for anger detection. Here, band energy is calculated within time windows, and is continuously adjusted based on classified peak amplitudes. Although this technique has a lower classification accuracy than the offline method, it is quite promising as it is well-suited for wearable monitoring and long-term stress management.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116874597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227591
First A. Avinash Kaur, Second B. Arti Kapil, Third C. Ravikrishnan Elangovan, Fourth D. Sandeep Jha, Fifth E. Dinesh Kalyanasundaram
Diseases such as enteric fever continues to be major cause of deaths globally, particularly in poor resource settings. Traditional cell viability test using bacterial culture method followed by confirmatory biochemical tests such as motility, triple sugar iron agar (TSI), citrate, urease test, agglutination tests, forms the gold standard method for diagnosis of enteric fever. However, these existing practices are time consuming. Highly sensitive detection of Salmonella typhi (S. typhi) in blood of 50 CFU/mL was achieved using our protocol involving a magnetic nanoparticle based preconcentration, a loop mediated isothermal amplification assay (LAMP) for signal augmentation and signal detection using an in-house designed optical detection system. Primers specific for STY2879 gene were used to amplify the nucleic acid isolated from S. typhi cells. The protocol involves detection of nucleic acid amplification for both pre and four hour post-incubation that confirms (a) cell viability and (b) specificity of S. typhi and (c) quantification of S. typhi. No cross reactivity of the primers were observed against 106 CFU/mL of common pathogenic bacterial species found in blood such as such as E. coli, P. aeruginosa, S. aureus, A baumanni, E. faecalis, S. paratyphi A and K. pneumonia. This detection system shows a promising future in the field of food and medical diagnostics. The instrument can be extended to other pathogens in the future with modification of the primers and minimal modification of the pre-concentration and lysis protocol.
{"title":"Highly-sensitive detection of Salmonella typhi in human blood using a portable optical system for detection of nucleic acids amplification","authors":"First A. Avinash Kaur, Second B. Arti Kapil, Third C. Ravikrishnan Elangovan, Fourth D. Sandeep Jha, Fifth E. Dinesh Kalyanasundaram","doi":"10.1109/HIC.2017.8227591","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227591","url":null,"abstract":"Diseases such as enteric fever continues to be major cause of deaths globally, particularly in poor resource settings. Traditional cell viability test using bacterial culture method followed by confirmatory biochemical tests such as motility, triple sugar iron agar (TSI), citrate, urease test, agglutination tests, forms the gold standard method for diagnosis of enteric fever. However, these existing practices are time consuming. Highly sensitive detection of Salmonella typhi (S. typhi) in blood of 50 CFU/mL was achieved using our protocol involving a magnetic nanoparticle based preconcentration, a loop mediated isothermal amplification assay (LAMP) for signal augmentation and signal detection using an in-house designed optical detection system. Primers specific for STY2879 gene were used to amplify the nucleic acid isolated from S. typhi cells. The protocol involves detection of nucleic acid amplification for both pre and four hour post-incubation that confirms (a) cell viability and (b) specificity of S. typhi and (c) quantification of S. typhi. No cross reactivity of the primers were observed against 106 CFU/mL of common pathogenic bacterial species found in blood such as such as E. coli, P. aeruginosa, S. aureus, A baumanni, E. faecalis, S. paratyphi A and K. pneumonia. This detection system shows a promising future in the field of food and medical diagnostics. The instrument can be extended to other pathogens in the future with modification of the primers and minimal modification of the pre-concentration and lysis protocol.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125718274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/HIC.2017.8227624
Shih-Kai Lin, Yu-Shan Lin, Chin-Yew Lin, H. Chiueh
Epilepsy is a common neural disorder disease; about 1.7% of the global population has epilepsy. Most patients take antiepileptic drugs to reduce their seizures. Among them, nearly one-third of the patients are drug-resistant epilepsy. The alternative treatment is the resection surgery of removing the epileptogenic zone. However, all above patients will still have some seizures, which will influence the patients' quality-of-life, and further introduce danger and inconvenience to patients and people around. This paper presents the design and develop of the smart headband for epileptic seizure detection. The headband consists of a textile headband with flexible print circuit (FPC) inside, and fabric electrodes on it. The whole system includes the following circuits: an analog front-end circuitry for electroencephalography (EEG) record, an epileptic seizure detection System-on-Chip (SoC), and a Bluetooth Low Energy (BLE) Chip. The result of designed circuits yields a compact and low-power design of smart headband for epileptic seizure detection which is suitable for wearable usage.
{"title":"A smart headband for epileptic seizure detection","authors":"Shih-Kai Lin, Yu-Shan Lin, Chin-Yew Lin, H. Chiueh","doi":"10.1109/HIC.2017.8227624","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227624","url":null,"abstract":"Epilepsy is a common neural disorder disease; about 1.7% of the global population has epilepsy. Most patients take antiepileptic drugs to reduce their seizures. Among them, nearly one-third of the patients are drug-resistant epilepsy. The alternative treatment is the resection surgery of removing the epileptogenic zone. However, all above patients will still have some seizures, which will influence the patients' quality-of-life, and further introduce danger and inconvenience to patients and people around. This paper presents the design and develop of the smart headband for epileptic seizure detection. The headband consists of a textile headband with flexible print circuit (FPC) inside, and fabric electrodes on it. The whole system includes the following circuits: an analog front-end circuitry for electroencephalography (EEG) record, an epileptic seizure detection System-on-Chip (SoC), and a Bluetooth Low Energy (BLE) Chip. The result of designed circuits yields a compact and low-power design of smart headband for epileptic seizure detection which is suitable for wearable usage.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121477890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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