2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)最新文献_第5页

Development of an extensible, wireless framework for personalized muscle rehabilitation 开发一种可扩展的无线框架，用于个性化肌肉康复

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962773

A. Jasuja, Varan Gupta, N. Sreenivasalu, Mary Liu, J. Monz, J. Nir, S. Bhasin

{"title":"Development of an extensible, wireless framework for personalized muscle rehabilitation","authors":"A. Jasuja, Varan Gupta, N. Sreenivasalu, Mary Liu, J. Monz, J. Nir, S. Bhasin","doi":"10.1109/HI-POCT45284.2019.8962773","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962773","url":null,"abstract":"Hemiparesis is progressive muscle weakness in one half of the body, commonly observed in traumatic brain injury or stroke patients. Usually, physiotherapists design in-person assistive exercises to restore muscle strength and range of motion for affected side of the patient. Alternatively, functional electrical stimulation (FES) devices have also been used, though the equipment is expensive, non-portable, and provides limited configurability for personalized rehabilitation. This paper presents a low-cost, open architecture framework that enables: a) Remote programming of muscle stimulation routine by therapist; b) Delivery of FES sequence to patient wirelessly, and c) Provide quantitative feedback (through Electromyogram (EMG)) on dynamics of exercised muscle with progressive rehabilitation of the patient. The extensible framework overcomes the major drawback of expensive, closed commercial systems, thereby allowing integration of multiple sensors to monitor muscle function. Rehabilitation efficacy feedback will allow an opportunity to personalize rehabilitation and increase patient compliance.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128122362","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}

引用次数: 1

HI-POCT 2019 Committees HI-POCT 2019委员会

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/hi-poct45284.2019.8962822

引用次数: 0

Predicting Dementia Risk Using Paralinguistic and Memory Test Features with Machine Learning Models 使用机器学习模型的副语言和记忆测试特征预测痴呆风险

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962887

Yilun You, Beena Ahmed, Polly Barr, K. Ballard, M. Valenzuela

引用次数: 4

Non-Invasive Screening Tool to Detect Anemia 检测贫血的无创筛查工具

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962856

A. Ajmal, S. Shankarnath, Mohamed Athif, E. Jayatunga

{"title":"Non-Invasive Screening Tool to Detect Anemia","authors":"A. Ajmal, S. Shankarnath, Mohamed Athif, E. Jayatunga","doi":"10.1109/HI-POCT45284.2019.8962856","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962856","url":null,"abstract":"Hemoglobin concentration is a vital parameter used to detect abnormalities in the human body including anemia and polycythemia. Currently, invasive techniques are used for hemoglobin measurement despite their many disadvantages including discomfort and potential complications for the pregnant, elderly and pediatric patients. This research paper focuses on measuring the hemoglobin concentration without drawing blood. In this study, measurements were obtained from a total of 106 patients and a linear relationship was obtained between hemoglobin concentration measured using the invasive technique (Hb) and the modulation ratio (R) calculated using red light and near-IR spectroscopy. The effect of confounding factors of gender and age were studied in this relationship. Based on the mathematical model developed, a non-invasive screening tool was developed to determine hemoglobin concentration. The device was evaluated using the 22 test subjects. The state-of-the-art hemoglobin measuring techniques do not facilitate continuous and remote monitoring which is essential in a point of care screening device. The proposed non-invasive device has the advantages of prevention of infections, physical pain, and the low operational or maintenance costs while being portable.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124380624","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}

引用次数: 8

Robust Discrimination of Phonocardiogram Signal with Normal Heart Sounds and Murmur Using a Multiscale Frequency Analysis 基于多尺度频率分析的心音图信号与正常心音和杂音的鲁棒区分

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962884

Divaakar Siva Baala Sundaram, Suganti Shivaram, R. Balasubramani, Anjani Muthyala, S. P. Arunachalam

{"title":"Robust Discrimination of Phonocardiogram Signal with Normal Heart Sounds and Murmur Using a Multiscale Frequency Analysis","authors":"Divaakar Siva Baala Sundaram, Suganti Shivaram, R. Balasubramani, Anjani Muthyala, S. P. Arunachalam","doi":"10.1109/HI-POCT45284.2019.8962884","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962884","url":null,"abstract":"Electrical recordings of the heart sounds namely, the phonocardiogram (PCG) signals contain information regarding the heart condition of diagnostic importance. Characteristic features of PCG signals have been explored using several automatic detection algorithms to aid in disease diagnosis. A major limitation is that, many of these methods have been demonstrated only on PCG clean signals with limited test data that lacks variety to provide information of diagnostic importance. A more robust method to characterize PCG signal is required that can aid in discriminating normal and diseased heart conditions such as heart murmur etc. In this work, it was hypothesized that a multiscale frequency (MSF) analysis can discriminate normal PCG and PCG with murmur based on their varying frequency content. 13 samples of normal PCG and heart sound signal with murmur from Peter Bentley Heart Sounds Database sampled at 44.1 kHz were used for analysis. A 4th order Butterworth lowpass filter was designed with cutoff frequency at 200 Hz to remove higher frequency noise and MSF estimation was performed on the filtered dataset using custom MATLAB software. Mann-Whitney test was performed for statistical significance at p < 0.05. The mean MSF for normal PCG was 108.94±13.38 Hz and the mean MSF for murmur heart sound signal was 47.71±16.31 Hz. MSF was significantly different between normal and murmur sound signal with p < 0.01. Validation of this technique with larger dataset is required. MSF technique can discriminate normal PCG and murmur sound signal. The results motivate the analysis and comparison of normal PCG’s with different cardiac conditions that can aid in disease diagnosis.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129189126","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}

引用次数: 0

HI-POCT 2019 Sponsors HI-POCT 2019赞助商

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/hi-poct45284.2019.8962760

引用次数: 0

Point-of-care 3D body-mapping for determining total body surface area of severely burned patients 用于确定严重烧伤患者体表总面积的即时三维体图绘制

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-11-01 DOI: 10.1109/HI-POCT45284.2019.8962792

Julia Loegering, Kevin Krause, Jesse Ahlquist, Kevin Webb, Karen Xu, N. Tran, D. Greenhalgh, T. Palmieri

{"title":"Point-of-care 3D body-mapping for determining total body surface area of severely burned patients","authors":"Julia Loegering, Kevin Krause, Jesse Ahlquist, Kevin Webb, Karen Xu, N. Tran, D. Greenhalgh, T. Palmieri","doi":"10.1109/HI-POCT45284.2019.8962792","DOIUrl":"https://doi.org/10.1109/HI-POCT45284.2019.8962792","url":null,"abstract":"Total body surface area (TBSA) is a critical biometric for accurate body fluid restoration and drug dosing in medical treatments. However, current clinical equation calculations of TBSA are highly inaccurate, resulting in error up to 25%. Within burn care, this error leads to misinformed fluid resuscitation that result in increased medical complications. Our team sought to combine recently developed mathematical equations that are clinically unutilized with 3D scanning methods to better the accuracy of TBSA calculations in treatment. To bridge the gap between modern TBSA equations and the clinic, we developed an algorithm that indexes an equation best suited to a patient according to inputs such as age, height and weight. For patients that cannot be matched to an appropriate equation, our team developed a time-of-flight scanning protocol to capture 3D models of the human body. From these models, TBSA can be extrapolated finite analysis deconstruction and image processing tools. Our scanning device reduced error of TBSA to an average of 4% across all scanned subjects and it proved to be one of the first 3D scanning devices compatible to the clinic workflow.","PeriodicalId":269346,"journal":{"name":"2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133374077","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}

引用次数: 0

Harnessing the Power of Deep Learning Methods in Healthcare: Neonatal Pain Assessment from Crying Sound 在医疗保健中利用深度学习方法的力量:从哭声中评估新生儿疼痛

2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT) Pub Date : 2019-09-05 DOI: 10.1109/HI-POCT45284.2019.8962827

Md Sirajus Salekin, Ghada Zamzami, Rahul Paul, Dmitry Goldgof, R. Kasturi, T. Ho, Yu Sun

引用次数: 7