Pub Date : 2016-12-27DOI: 10.1109/HIC.2016.7797708
S. P. Arunachalam, S. Kapa, S. Mulpuru, P. Friedman, E. Tolkacheva
Efficient and robust control of cardiac pacemaker is essential for providing life-saving control action to regulate Heart Rate (HR) in a dynamic environment. Several controller designs involving proportional-integral-derivative (PID) and fuzzy logic controllers (FLC) have been reported but each have their limitations to face the dynamic challenge of regulating HR. Fractional-order control (FOC) systems provide controllers that are described by fractional-order differential equations that offers fine tuning of the control parameters to provide robust and efficient performance. In this work a robust fractional-order PID (FOPID) controller is designed based on Ziegler-Nichols tuning method. The stable FOPID controller outperformed PID controllers with different tuning methods and also the FLC in terms of rise time, settling time and % overshoot. The FOPID controller also demonstrated feasibility for rate-adaptive pacing. However, the FOPID controller designed in this work is not optimal and is limited by the tuning procedure. More efficient design using optimization techniques such as particle swarm intelligence or genetic algorithm tuning can offer optimal control of the cardiac pacemaker.
{"title":"Intelligent fractional-order PID (FOPID) heart rate controller for cardiac pacemaker","authors":"S. P. Arunachalam, S. Kapa, S. Mulpuru, P. Friedman, E. Tolkacheva","doi":"10.1109/HIC.2016.7797708","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797708","url":null,"abstract":"Efficient and robust control of cardiac pacemaker is essential for providing life-saving control action to regulate Heart Rate (HR) in a dynamic environment. Several controller designs involving proportional-integral-derivative (PID) and fuzzy logic controllers (FLC) have been reported but each have their limitations to face the dynamic challenge of regulating HR. Fractional-order control (FOC) systems provide controllers that are described by fractional-order differential equations that offers fine tuning of the control parameters to provide robust and efficient performance. In this work a robust fractional-order PID (FOPID) controller is designed based on Ziegler-Nichols tuning method. The stable FOPID controller outperformed PID controllers with different tuning methods and also the FLC in terms of rise time, settling time and % overshoot. The FOPID controller also demonstrated feasibility for rate-adaptive pacing. However, the FOPID controller designed in this work is not optimal and is limited by the tuning procedure. More efficient design using optimization techniques such as particle swarm intelligence or genetic algorithm tuning can offer optimal control of the cardiac pacemaker.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133070272","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 : 2016-11-09DOI: 10.1109/HIC.2016.7797722
Nikolaos Papachristou, C. Miaskowski, P. Barnaghi, R. Maguire, Nazli Farajidavar, B. Cooper, Xiao Hu
Symptom Cluster Research is a major topic in Cancer Symptom Science. In spite of the several statistical and clinical approaches in this domain, there is not a consensus on which method performs better. Identifying a generally accepted analytical method is important in order to be able to utilize and process all the available data. In this paper we report a secondary analysis on cancer symptom data, comparing the performance of five Machine Learning (ML) clustering algorithms in doing so. Based on how well they separate specific subsets of symptom measurements we select the best of them and proceed to compare its performance with the Latent Class Analysis (LCA) method. This analysis is a part of an ongoing study for identifying suitable Machine Learning algorithms to analyse and predict cancer symptoms in cancer treatment.
{"title":"Comparing machine learning clustering with latent class analysis on cancer symptoms' data","authors":"Nikolaos Papachristou, C. Miaskowski, P. Barnaghi, R. Maguire, Nazli Farajidavar, B. Cooper, Xiao Hu","doi":"10.1109/HIC.2016.7797722","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797722","url":null,"abstract":"Symptom Cluster Research is a major topic in Cancer Symptom Science. In spite of the several statistical and clinical approaches in this domain, there is not a consensus on which method performs better. Identifying a generally accepted analytical method is important in order to be able to utilize and process all the available data. In this paper we report a secondary analysis on cancer symptom data, comparing the performance of five Machine Learning (ML) clustering algorithms in doing so. Based on how well they separate specific subsets of symptom measurements we select the best of them and proceed to compare its performance with the Latent Class Analysis (LCA) method. This analysis is a part of an ongoing study for identifying suitable Machine Learning algorithms to analyse and predict cancer symptoms in cancer treatment.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133612137","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797702
Harrison Hall, Abeer Syed, John X. J. Zhang
We report a semiquantitative readout technique using structured Quick Response (QR) codes partially patterned with colorimetric assay. This allows error-corrected readout at point-of-care (POC) the assay using mobile devices while transparently enabling remote tabulation of population-level statistics through analysis of web traffic.
{"title":"Two-dimensional, error-corrected barcode readout for point-of-care colorimetrie assays","authors":"Harrison Hall, Abeer Syed, John X. J. Zhang","doi":"10.1109/HIC.2016.7797702","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797702","url":null,"abstract":"We report a semiquantitative readout technique using structured Quick Response (QR) codes partially patterned with colorimetric assay. This allows error-corrected readout at point-of-care (POC) the assay using mobile devices while transparently enabling remote tabulation of population-level statistics through analysis of web traffic.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126877560","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797694
C. Hafer-Macko, J. Naumes, R. Macko, A. Roy
Myasthenia gravis (MG) is a rare neuromuscular condition characterized by weakness and fatigue. Exertional fatigue in MG provokes caution with exercise advice. There is no consensus on how to implement safe and effective exercise or rehabilitation for MG. To address this gap, we developed an MG specific, progressive exercise program that focuses on the muscles that are most affected. The program combines aerobic training, muscular endurance, and pulmonary rehabilitation to improve function, energy efficiency, and cardio-pulmonary capacity. Our Interactive Video Exercise Tele-rehabilitation (IVET) platform embeds our MG specific exercises, adapted to each client's capacity. A video avatar guides home exercises with adjustable metronome pacing, while video capturing the client's performance for unprecedented understanding of desired body mechanics and to enhance coach feedback. This two-way interactive wireless platform increases access to expert oversight and enhances safety. IVET was pilot tested at the point-of-care in neurology and infusion clinics to assess clients' acceptance of this technology, as well as client and coach/therapist ratings on client safety and competency for each exercise. Twelve clients with a broad range of age and MG severity were enrolled. Survey of client's technology acceptance for home IVET exercise used a nominal 10-point scale and demonstrated high rating for enjoyment, interest, confidence, safety, perceived value, and increased frequency of structured exercise. Further studies are needed to determine the treatment fidelity, safety, and efficacy of IVET as a virtual therapist in the home to improve function and health for individuals with MG.
{"title":"Technology platform for tele-rehabilitation implementation in Mysathenia gravis at the point-of-care","authors":"C. Hafer-Macko, J. Naumes, R. Macko, A. Roy","doi":"10.1109/HIC.2016.7797694","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797694","url":null,"abstract":"Myasthenia gravis (MG) is a rare neuromuscular condition characterized by weakness and fatigue. Exertional fatigue in MG provokes caution with exercise advice. There is no consensus on how to implement safe and effective exercise or rehabilitation for MG. To address this gap, we developed an MG specific, progressive exercise program that focuses on the muscles that are most affected. The program combines aerobic training, muscular endurance, and pulmonary rehabilitation to improve function, energy efficiency, and cardio-pulmonary capacity. Our Interactive Video Exercise Tele-rehabilitation (IVET) platform embeds our MG specific exercises, adapted to each client's capacity. A video avatar guides home exercises with adjustable metronome pacing, while video capturing the client's performance for unprecedented understanding of desired body mechanics and to enhance coach feedback. This two-way interactive wireless platform increases access to expert oversight and enhances safety. IVET was pilot tested at the point-of-care in neurology and infusion clinics to assess clients' acceptance of this technology, as well as client and coach/therapist ratings on client safety and competency for each exercise. Twelve clients with a broad range of age and MG severity were enrolled. Survey of client's technology acceptance for home IVET exercise used a nominal 10-point scale and demonstrated high rating for enjoyment, interest, confidence, safety, perceived value, and increased frequency of structured exercise. Further studies are needed to determine the treatment fidelity, safety, and efficacy of IVET as a virtual therapist in the home to improve function and health for individuals with MG.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123804194","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797727
Varsha Wahane, P. Ingole
The Wireless Body Area Network (WBAN) is emerging by leaps and bound due to tremendous evolutions in sensors and wireless communication technologies. For WBAN technology improvisation, researchers are mainly concentrating on technical parameters of health monitoring to make it interactive and real time based. A WBAN is an integration of Wireless Sensor Networks (WSNs) to connect various Biomedical Wireless Sensors (BWSs) located inside and outside of the human body to collect and transmit vital signals. The collected biomedical data is send to the hospitals and medical centres for therapeutic, diagnostic analysis and treatment. An electrocardiogram (ECG), a non-invasive mechanism, is widely used to establish medical diagnosis of heart diseases in health care systems. This paper presents a microcontroller ARM7 based health monitoring system intended to monitor and to early detect situations when heart rate and blood oxygen level are out of their safe ranges. The main objective of this proposal is to prevent emergency situations by informing the patient to take actions before patient's health condition get worse leading to emergency medical care. This system employs a programmable ARM7 for confab the bio-signal to determine the condition of heart. If any abnormalities are discovered from patient's heart parameters, the system sends alarm to the doctor. The system ensures wireless transmission of ECG signal to the Medical Server (doctor's PC) through Bluetooth and Android platform. This endows doctor to have visual description of patient's ECG on Medical Server and if critical condition exists, system will send alert messages to the doctor on his mobile phone even if doctor is away from Medical server. The experimental result shows that the device is compact, cheap, user friendly and useful.
{"title":"An Android based wireless ECG monitoring system for cardiac arrhythmia","authors":"Varsha Wahane, P. Ingole","doi":"10.1109/HIC.2016.7797727","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797727","url":null,"abstract":"The Wireless Body Area Network (WBAN) is emerging by leaps and bound due to tremendous evolutions in sensors and wireless communication technologies. For WBAN technology improvisation, researchers are mainly concentrating on technical parameters of health monitoring to make it interactive and real time based. A WBAN is an integration of Wireless Sensor Networks (WSNs) to connect various Biomedical Wireless Sensors (BWSs) located inside and outside of the human body to collect and transmit vital signals. The collected biomedical data is send to the hospitals and medical centres for therapeutic, diagnostic analysis and treatment. An electrocardiogram (ECG), a non-invasive mechanism, is widely used to establish medical diagnosis of heart diseases in health care systems. This paper presents a microcontroller ARM7 based health monitoring system intended to monitor and to early detect situations when heart rate and blood oxygen level are out of their safe ranges. The main objective of this proposal is to prevent emergency situations by informing the patient to take actions before patient's health condition get worse leading to emergency medical care. This system employs a programmable ARM7 for confab the bio-signal to determine the condition of heart. If any abnormalities are discovered from patient's heart parameters, the system sends alarm to the doctor. The system ensures wireless transmission of ECG signal to the Medical Server (doctor's PC) through Bluetooth and Android platform. This endows doctor to have visual description of patient's ECG on Medical Server and if critical condition exists, system will send alert messages to the doctor on his mobile phone even if doctor is away from Medical server. The experimental result shows that the device is compact, cheap, user friendly and useful.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114774446","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797698
O. Dehzangi, M. Mohammadi, Y. Li
The aim of this study is to develop a platform to monitor compliance with brace treatment in patients with scoliosis. Scoliosis is a curvature of the spine that frequently occurs in adolescents. Nonoperative treatment with a thoracolumbosacral orthosis (TLSO) is widely used. However, a brace that is not worn correctly is not effective at controlling scoliosis, regardless of the duration of brace wear. As a solution for monitoring these patients, we developed a low power multi-modal sensor board capable of: 1) logging pressure distribution inside the brace using analog pressure sensors and 2) detecting different activities that the patient is involved in using accelerometer sensor. We employ the two modalities of signals recorded from the brace to achieve high precision compliance monitoring system. Our data processing algorithm suite includes a two-stage data classification design. In the first stage, we detect six predefined activities including: standing, sitting, walking, running, lying down, and climbing the stairs using an embedded motion sensor. In the second stage, we detect four levels of brace tightness based on features extracted from internal force sensors and activity specific models. Our results demonstrated high levels of accuracy for activity and tightness level classification.
{"title":"Smart brace for monitoring patients with scoliosis using a multimodal sensor board solution","authors":"O. Dehzangi, M. Mohammadi, Y. Li","doi":"10.1109/HIC.2016.7797698","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797698","url":null,"abstract":"The aim of this study is to develop a platform to monitor compliance with brace treatment in patients with scoliosis. Scoliosis is a curvature of the spine that frequently occurs in adolescents. Nonoperative treatment with a thoracolumbosacral orthosis (TLSO) is widely used. However, a brace that is not worn correctly is not effective at controlling scoliosis, regardless of the duration of brace wear. As a solution for monitoring these patients, we developed a low power multi-modal sensor board capable of: 1) logging pressure distribution inside the brace using analog pressure sensors and 2) detecting different activities that the patient is involved in using accelerometer sensor. We employ the two modalities of signals recorded from the brace to achieve high precision compliance monitoring system. Our data processing algorithm suite includes a two-stage data classification design. In the first stage, we detect six predefined activities including: standing, sitting, walking, running, lying down, and climbing the stairs using an embedded motion sensor. In the second stage, we detect four levels of brace tightness based on features extracted from internal force sensors and activity specific models. Our results demonstrated high levels of accuracy for activity and tightness level classification.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125572389","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797707
Huiquan Wang, Hongming Xu, S. N. Ahmed, M. Mandai
Cavernous malformation or cavernomas is abnormal development of brain blood vessels and affect an estimated 0.5% of the world population. These could cause seizures, intracerebral hemorrhage and various neurological deficits based on the location of the lesion. Radiologists usually analysis brain magnetic resonance (MR) images to detect cavernomas. However, automatic detection of cavernomas by computer has not been investigated enough. This paper proposes a computer aided cavernomas detection method based on MR images analysis. The proposed method includes three steps: brain extraction based on deformable contour (to remove the non-brain tissues from image), template matching (to find suspected cavernomas regions) and post-processing (to get rid of false positives based on size, shape and brightness information). The performance of the proposed technique is evaluated and a sensitivity of 0.92 is obtained after testing.
{"title":"Computer aided detection of cavernous malformation in T2-weighted brain MR images","authors":"Huiquan Wang, Hongming Xu, S. N. Ahmed, M. Mandai","doi":"10.1109/HIC.2016.7797707","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797707","url":null,"abstract":"Cavernous malformation or cavernomas is abnormal development of brain blood vessels and affect an estimated 0.5% of the world population. These could cause seizures, intracerebral hemorrhage and various neurological deficits based on the location of the lesion. Radiologists usually analysis brain magnetic resonance (MR) images to detect cavernomas. However, automatic detection of cavernomas by computer has not been investigated enough. This paper proposes a computer aided cavernomas detection method based on MR images analysis. The proposed method includes three steps: brain extraction based on deformable contour (to remove the non-brain tissues from image), template matching (to find suspected cavernomas regions) and post-processing (to get rid of false positives based on size, shape and brightness information). The performance of the proposed technique is evaluated and a sensitivity of 0.92 is obtained after testing.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131126718","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797697
Hany M Arafa, U. Obahiagbon, D. Kullman, Fatima-Joyce Dominguez, Abigail Magee, J. Christen
In this work we present a system designed for continuous assessment of tumor cell extracellular pH using a fabricated quartz extended-gate ion-sensitive field effect transistor (EGFET). The extended gate structure was fabricated by patterning gold on a quartz substrate creating a pseudo-reference electrode and sensor below a Si3N4 sensing membrane. Various electrode geometries and configurations were created and each pattern was characterized. A readout/data acquisition system was designed to convert the current output of the EGFET to a voltage that was recorded using a low-power single board computer, which performed a hard "reset" before every data acquisition interval. This setup was able to monitor the viability of SKBR3 mammary gland tumor cells treated with staurosporine. Over a span of 8 hours, the autonomous data acquisition system recorded a steady decrease in cell viability. Results were verified with periodic cell culture images. Future applications include design of an extended gate EGFET array, which allows for accurate monitoring of individual cell cultures.
{"title":"Characterization and application of a discrete quartz extended-gate ISFET for the assessment of tumor cell viability","authors":"Hany M Arafa, U. Obahiagbon, D. Kullman, Fatima-Joyce Dominguez, Abigail Magee, J. Christen","doi":"10.1109/HIC.2016.7797697","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797697","url":null,"abstract":"In this work we present a system designed for continuous assessment of tumor cell extracellular pH using a fabricated quartz extended-gate ion-sensitive field effect transistor (EGFET). The extended gate structure was fabricated by patterning gold on a quartz substrate creating a pseudo-reference electrode and sensor below a Si3N4 sensing membrane. Various electrode geometries and configurations were created and each pattern was characterized. A readout/data acquisition system was designed to convert the current output of the EGFET to a voltage that was recorded using a low-power single board computer, which performed a hard \"reset\" before every data acquisition interval. This setup was able to monitor the viability of SKBR3 mammary gland tumor cells treated with staurosporine. Over a span of 8 hours, the autonomous data acquisition system recorded a steady decrease in cell viability. Results were verified with periodic cell culture images. Future applications include design of an extended gate EGFET array, which allows for accurate monitoring of individual cell cultures.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133094353","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797714
M. Cremer, Jillian Garai, L. Taxa, M. Salinas, J. Felix, K. Alfaro, Michael Haas, Albert Zevallos
The development of human papillomavirus screening tests is outpacing the introduction of new treatment technologies. In low-resource settings, there is an urgent need for treatment methods that are accessible, affordable, and sustainable in areas with limited medical infrastructure. The gasless CryoPen® Cryosurgical System overcomes the limitations of traditional gas-based cryotherapy and is being adapted specifically for use in low-resource areas. The innovative device demonstrates exceptional portability, durability, and efficiency. The adapted CryoPen® is a simple, safe, and practical option for treatment of cervical precancer in settings that cannot support gas-based cryotherapy.
{"title":"CryoPen®, A gasless cryotherapy system adapted for low-resource settings","authors":"M. Cremer, Jillian Garai, L. Taxa, M. Salinas, J. Felix, K. Alfaro, Michael Haas, Albert Zevallos","doi":"10.1109/HIC.2016.7797714","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797714","url":null,"abstract":"The development of human papillomavirus screening tests is outpacing the introduction of new treatment technologies. In low-resource settings, there is an urgent need for treatment methods that are accessible, affordable, and sustainable in areas with limited medical infrastructure. The gasless CryoPen® Cryosurgical System overcomes the limitations of traditional gas-based cryotherapy and is being adapted specifically for use in low-resource areas. The innovative device demonstrates exceptional portability, durability, and efficiency. The adapted CryoPen® is a simple, safe, and practical option for treatment of cervical precancer in settings that cannot support gas-based cryotherapy.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131858595","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 : 2016-11-01DOI: 10.1109/HIC.2016.7797688
Mahan Rahimi, A. Blaber, C. Menon
While compression therapy is the cornerstone in managing leg venous disorders, the applied pressure has to be in specific ranges in order to have an effective treatment. Medical bandages and compression stockings lack an embedded pressure measurement system. The listed class of compression for medical stockings is not utterly reliable, and achieving desired pressure profiles in medical bandages is dependent solely on the bandaging skills of clinicians. Moreover, after the recipients of compression products leave medical centers, there exists no way to continuously assess the changes in sub-bandage pressure that might occur due to movements and physiological changes of the lower extremities. Thus there is a need for a valid and reliable measurement system that can be integrated into compression products for continuous monitoring of the interface pressure. In the current study, force-sensing resistors (FSRs®), which are portable, thin, flexible, low-cost, and easy-to-use sensors, were investigated. FSRs, like many other flexible resistive sensors, are known for their qualitative rather than quantitative measurements. Therefore, they should be validated for clinical use. In this study, the FSRs were first calibrated on different surfaces, including human leg, and then evaluated in measuring interface pressures in situ. The preliminary investigations showed promising results.
{"title":"Towards the evaluation of force-sensing resistors for in situ measurement of interface pressure during leg compression therapy","authors":"Mahan Rahimi, A. Blaber, C. Menon","doi":"10.1109/HIC.2016.7797688","DOIUrl":"https://doi.org/10.1109/HIC.2016.7797688","url":null,"abstract":"While compression therapy is the cornerstone in managing leg venous disorders, the applied pressure has to be in specific ranges in order to have an effective treatment. Medical bandages and compression stockings lack an embedded pressure measurement system. The listed class of compression for medical stockings is not utterly reliable, and achieving desired pressure profiles in medical bandages is dependent solely on the bandaging skills of clinicians. Moreover, after the recipients of compression products leave medical centers, there exists no way to continuously assess the changes in sub-bandage pressure that might occur due to movements and physiological changes of the lower extremities. Thus there is a need for a valid and reliable measurement system that can be integrated into compression products for continuous monitoring of the interface pressure. In the current study, force-sensing resistors (FSRs®), which are portable, thin, flexible, low-cost, and easy-to-use sensors, were investigated. FSRs, like many other flexible resistive sensors, are known for their qualitative rather than quantitative measurements. Therefore, they should be validated for clinical use. In this study, the FSRs were first calibrated on different surfaces, including human leg, and then evaluated in measuring interface pressures in situ. The preliminary investigations showed promising results.","PeriodicalId":333642,"journal":{"name":"2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124797127","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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