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Kim SC, Kim S. Development of a Dog Health Score Using an Artificial Intelligence Disease Prediction Algorithm Based on Multifaceted Data. Animals (Basel) 2024; 14:256. [PMID: 38254424 PMCID: PMC10812422 DOI: 10.3390/ani14020256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/04/2024] [Accepted: 01/09/2024] [Indexed: 01/24/2024] Open
Abstract
Detecting aberrant behaviors in dogs or observing emotional interactions between a dog and its owner may serve as indicators of potential canine diseases. However, dog owners typically struggle to assess or predict the health status of their pets independently. Consequently, there is a demand for a methodology enabling owners to evaluate their dogs' health based on everyday behavioral data. To address this need, we gathered individual canine data, including three months of standard daily activities (such as scratching, licking, swallowing, and sleeping), to train an AI model. This model identifies abnormal behaviors and quantifies each behavior as a numerical score, termed the "Health Score". This score is categorized into ten levels, where a higher score indicates a healthier state. Scores below 5 warrant medical consultation, while those above 5 are deemed healthy. We validated the baseline value of the Health Score against veterinarian diagnoses, achieving an 87.5% concordance rate. This validation confirms the reliability of the Health Score, which assesses canine health through daily activity monitoring, and is expected to significantly benefit dog owners who face challenges in determining the health status of their pets.
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Affiliation(s)
- Seon-Chil Kim
- Department of Biomedical Engineering, Keimyung University, 1095 Dalgubeol-daero, Daegu 42601, Republic of Korea
| | - Sanghyun Kim
- DDcares Inc., #710 815 Daewangpangyo-ro, Sujeong-gu, Seongnam-si 30119, Republic of Korea;
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Wong AKC, Tso WC, Su JJ, Hui VCC, Chow KKS, Wong SM, Wong BB, Wong FKY. Effectiveness of support from community health workers on the sustained use of a wearable monitoring device among community-dwelling older adults: A randomized trial protocol. PLoS One 2023; 18:e0294517. [PMID: 38134126 PMCID: PMC10745171 DOI: 10.1371/journal.pone.0294517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 10/30/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Wearable monitoring devices, such as smartwatches and fitness bands, are health technologies for enhancing self-care management among community-dwelling older adults. While the evidence suggests that these devices can promote health, older adults often struggle to use them over the long term. Community health workers can effectively motivate older adults to change their health behaviors. This study proposes an intervention involving community health workers as peer supporters to promote sustained daily use of wearable monitoring devices among community-dwelling older adults. METHODS The intervention group in this randomized controlled trial will receive the Live with Wearable Monitoring Device program from trained community health workers with the support of a nurse and social workers through a one-time home visit and regular phone calls. The control group will receive only the wearable monitoring device. Data will be collected at baseline, 1 month, 3 months, and 6 months. DISCUSSION Merely providing older adults with wearable monitoring devices may not lead to the realization of the potential health benefits of these devices, as long-term usage can be challenging. The results of this trial can provide evidence for a new approach to enhancing self-management and community healthcare among community-dwelling older adults, ultimately improving their health outcomes. IMPACT Wearable monitoring devices not only enable real-time monitoring of vital signs, but can also support tailored messaging and facilitate virtual communication between users and healthcare professionals. Despite considerable health benefits, there is evidence showing that older adults largely stop using them after a few months. This study is the first to use a peer support approach to help older adults incorporate a wearable monitoring device in their daily routines in conjunction with goal setting and regular reminders. This will boost the self-care ability of the older adults, allowing them to continue physically functioning in the community. TRIAL REGISTRATION This study was prospectively registered at clinicaltrials.gov (identifier: NCT05269303). Registration date: 24/2/2022.
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Affiliation(s)
| | - Wai Chun Tso
- School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | - Jing Jing Su
- School of Nursing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | | | - Karen Kit Sum Chow
- Elderly Center Division, Hong Kong Lutheran Social Service, Ho Man Tin, Hong Kong
| | - Siu Man Wong
- Elderly Center Division, Hong Kong Lutheran Social Service, Ho Man Tin, Hong Kong
| | - Bonnie Bo Wong
- Elderly Center Division, Hong Kong Lutheran Social Service, Ho Man Tin, Hong Kong
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Pineda-Alpizar F, Arriola-Valverde S, Vado-Chacón M, Sossa-Rojas D, Liu H, Zheng D. Real-Time Evaluation of Time-Domain Pulse Rate Variability Parameters in Different Postures and Breathing Patterns Using Wireless Photoplethysmography Sensor: Towards Remote Healthcare in Low-Resource Communities. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23094246. [PMID: 37177450 PMCID: PMC10181559 DOI: 10.3390/s23094246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/20/2023] [Accepted: 04/23/2023] [Indexed: 05/15/2023]
Abstract
Photoplethysmography (PPG) signals have been widely used in evaluating cardiovascular biomarkers, however, there is a lack of in-depth understanding of the remote usage of this technology and its viability for underdeveloped countries. This study aims to quantitatively evaluate the performance of a low-cost wireless PPG device in detecting ultra-short-term time-domain pulse rate variability (PRV) parameters in different postures and breathing patterns. A total of 30 healthy subjects were recruited. ECG and PPG signals were simultaneously recorded in 3 min using miniaturized wearable sensors. Four heart rate variability (HRV) and PRV parameters were extracted from ECG and PPG signals, respectively, and compared using analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. In addition, the data loss was calculated as the percentage of missing sampling points. Posture did not present statistical differences across the PRV parameters but a statistical difference between indicators was found. Strong variation was found for the RMSSD indicator in the standing posture. The sitting position in both breathing patterns demonstrated the lowest data loss (1.0 ± 0.6 and 1.0 ± 0.7) and the lowest percentage of different factors for all indicators. The usage of commercial PPG and BLE devices can allow the reliable extraction of the PPG signal and PRV indicators in real time.
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Affiliation(s)
- Felipe Pineda-Alpizar
- Industrial Design Engineering Department, Costa Rica Institute of Technology, Cartago 7050, Costa Rica
| | - Sergio Arriola-Valverde
- Electronics Engineering Department, Costa Rica Institute of Technology, Cartago 7050, Costa Rica
| | - Mitzy Vado-Chacón
- Respiratory Therapy Department, Santa Paula University, San Jose 2633, Costa Rica
| | - Diego Sossa-Rojas
- Respiratory Therapy Department, Santa Paula University, San Jose 2633, Costa Rica
| | - Haipeng Liu
- Center of Intelligent Healthcare, Coventry University, Coventry CV1 5FB, UK
| | - Dingchang Zheng
- Center of Intelligent Healthcare, Coventry University, Coventry CV1 5FB, UK
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Jiang X, Chen J, Yuan X, Lin Y, Chen Y, Li S, Jiang Q, Yu H, Du Q, Peng J. Feasibility of an Individualized mHealth Nutrition (iNutrition) Intervention for Post-Discharged Gastric Cancer Patients Following Gastrectomy: A Randomized Controlled Pilot Trial. Nutrients 2023; 15:nu15081883. [PMID: 37111102 PMCID: PMC10144256 DOI: 10.3390/nu15081883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/07/2023] [Accepted: 04/12/2023] [Indexed: 04/29/2023] Open
Abstract
(1) Background: A major challenge for post-discharged gastric cancer patients following gastrectomy is the impact of the anatomy change on decreased oral intake, nutritional status, and, ultimately, quality of life. The purpose of this study is to examine the feasibility and preliminary effects of an individualized mHealth nutrition (iNutrition) intervention in post-discharged gastric cancer patients following gastrectomy. (2) Methods: A mixed-method feasibility study with a parallel randomized controlled design was conducted. Patients were randomly assigned to either the iNutrition intervention group (n = 12) or the control group (n = 12). Participants completed measures at baseline (T0), four (T1), and twelve weeks (T2) post-randomization. (3) Results: Recruitment (33%) and retention (87.5%) rates along with high adherence and acceptability supported the feasibility of the iNutrition intervention for post-discharged gastric cancer patients following gastrectomy, echoed by the qualitative findings. The iNutrition intervention significantly improved participants' nutritional behavior (p = 0.005), energy intake (p = 0.038), compliance with energy requirements (p = 0.006), and compliance with protein requirements (p = 0.008). (4) Conclusions: The iNutrition intervention is feasible and potentially benefits post-discharged gastric cancer patients following gastrectomy. A larger trial is required to establish the efficacy of this approach. Trial Registration: 19 October 2022 Chinese Clinical Trial Registry, ChiCTR2200064807.
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Affiliation(s)
- Xiaohan Jiang
- School of Nursing, Sun Yat-sen University, Guangzhou 510006, China
| | - Jiamin Chen
- Department of Gastric Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
- Department of Clinical Nutrition, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
| | - Xiuhong Yuan
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510006, China
| | - Yijia Lin
- Department of Gastric Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
| | - Yingliang Chen
- Department of Gastric Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
| | - Sijia Li
- Department of Gastric Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
| | - Qiuxiang Jiang
- Department of Gastric Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
| | - Hong Yu
- Department of Gastric Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510006, China
| | - Qianqian Du
- School of Nursing, Sun Yat-sen University, Guangzhou 510006, China
| | - Junsheng Peng
- School of Nursing, Sun Yat-sen University, Guangzhou 510006, China
- Department of Gastric Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510006, China
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Muhsen IN, Rasheed OW, Habib EA, Alsaad RK, Maghrabi MK, Rahman MA, Sicker D, Wood WA, Beg MS, Sung AD, Hashmi SK. Current Status and Future Perspectives on the Internet of Things in Oncology. Hematol Oncol Stem Cell Ther 2023; 16:102-109. [PMID: 34687614 DOI: 10.1016/j.hemonc.2021.09.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 09/04/2021] [Accepted: 09/24/2021] [Indexed: 01/31/2023] Open
Abstract
The Internet of Things (IoT) has penetrated many aspects of everyday human life. The use of IoT in healthcare has been expanding over the past few years. In this review, we highlighted the current applications of IoT in the medical literature, along with the challenges and opportunities. IoT use mainly involves sensors and wearables, with potential applications in improving the quality of life, personal health monitoring, and diagnosis of diseases. Our literature review highlights that the current main application studied in the literature is physical activity tracking. In addition, we discuss the current technologies that would help IoT-enabled devices achieve safe, quick, and meaningful data transfer. These technologies include machine learning/artificial intelligence, 5G, and blockchain. Data on current IoT-enabled devices are still limited, and future research should address these devices' effect on patients' outcomes and the methods by which their integration in healthcare will avoid increasing costs.
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Affiliation(s)
- Ibrahim N Muhsen
- Department of Medicine, Houston Methodist Hospital, Houston, TX, USA
| | - Omar W Rasheed
- College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | - Eiad A Habib
- College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | - Rakan K Alsaad
- College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | | | - Md A Rahman
- Department of Cyber Security and Forensic Computing, University of Prince Mugrin, Medina, Saudi Arabia
| | - Douglas Sicker
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - William A Wood
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Muhammad S Beg
- Division of Hematology/Medical Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Anthony D Sung
- Division of Hematologic Malignancies and Cellular Therapy, Department of Medicine, Duke University School of Medicine, NC, USA
| | - Shahrukh K Hashmi
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.,Department of Medicine, Sheikh Shakbout Medical City, Abu Dhabi, United Arab Emirates
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Zhou D, Zhan Q, Wen X. How does digital life influence the health service use among rural residents? Evidence from China. Technol Health Care 2023; 31:2091-2106. [PMID: 37483027 DOI: 10.3233/thc-220631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
BACKGROUND The Healthy China strategy is an important development objective of the 14th Five-Year Plan and Vision 2035 in China, while health service use in rural China has been a weak link in this strategy. OBJECTIVE Nowadays, people's health service use will be influenced by digital technology due to the arrival of the Digital Age, and that is the reason why our interest is to discuss the effect of digital life on health service use among rural residents. METHODS We use the data from the China Family Panel Studies (CFPS) 2020 to examine the effect of digital life on health service use among rural residents, and we use Instrumental Variables method to control the endogenous problem and use KHB model to discuss the mechanism of this effect. RESULTS It was found that digital life has increased the health service use among rural residents significantly, and this result has been verified by robust test and Instrumental Variables method. Besides, digital life can increase health service use through the information channel effect and the health literacy effect indirectly. Moreover, digital life has a more significant impact on the residents with low social capital, low physical capital and low social trust, which represents the inclusivity of digital life. CONCLUSION The results of our paper will be helpful to examine the effect of the digital policy on promoting the health service use in rural China, and our findings will provide evidence of how to use digital life to enhance health service use among rural residents. Based on this, the government should take measures to eliminate the digital divide between urban and rural areas by promoting the level of digital life among rural residents, paying more attention to the digital literacy development among them, and forging ahead toward the great goal of the Healthy China under the Digital Age.
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Affiliation(s)
- Deshui Zhou
- School of Finance and Public Management, Anhui University of Finance & Economics, Bengbu, Anhui, China
| | - Qianqian Zhan
- School of Finance and Public Management, Anhui University of Finance & Economics, Bengbu, Anhui, China
| | - Xin Wen
- School of Humanities and Law (School of Public Administration), Yanshan University, Qinhuangdao, Hebei, China
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7
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Kosowicz L, Tran K, Khanh TT, Dang TH, Pham VA, Ta Thi Kim H, Thi Bach Duong H, Nguyen TD, Phuong AT, Le TH, Ta VA, Wickramasinghe N, Schofield P, Zelcer J, Pham Le T, Nguyen TA. Lessons for Vietnam on the use of digital technologies to support patient-centred care in low- and middle-income countries in the Asia Pacific Region: A scoping review (Preprint). J Med Internet Res 2022; 25:e43224. [PMID: 37018013 PMCID: PMC10132046 DOI: 10.2196/43224] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/11/2023] [Accepted: 02/01/2023] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND A rapidly aging population, a shifting disease burden and the ongoing threat of infectious disease outbreaks pose major concerns for Vietnam's health care system. Health disparities are evident in many parts of the country, especially in rural areas, and the population faces inequitable access to patient-centered health care. Vietnam must therefore explore and implement advanced solutions to the provision of patient-centered care, with a view to reducing pressures on the health care system simultaneously. The use of digital health technologies (DHTs) may be one of these solutions. OBJECTIVE This study aimed to identify the application of DHTs to support the provision of patient-centered care in low- and middle-income countries in the Asia-Pacific region (APR) and to draw lessons for Vietnam. METHODS A scoping review was undertaken. Systematic searches of 7 databases were conducted in January 2022 to identify publications on DHTs and patient-centered care in the APR. Thematic analysis was conducted, and DHTs were classified using the National Institute for Health and Care Excellence evidence standards framework for DHTs (tiers A, B, and C). Reporting was in line with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. RESULTS Of the 264 publications identified, 45 (17%) met the inclusion criteria. The majority of the DHTs were classified as tier C (15/33, 45%), followed by tier B (14/33, 42%) and tier A (4/33, 12%). At an individual level, DHTs increased accessibility of health care and health-related information, supported individuals in self-management, and led to improvements in clinical and quality-of-life outcomes. At a systems level, DHTs supported patient-centered outcomes by increasing efficiency, reducing strain on health care resources, and supporting patient-centered clinical practice. The most frequently reported enablers for the use of DHTs for patient-centered care included alignment of DHTs with users' individual needs, ease of use, availability of direct support from health care professionals, provision of technical support as well as user education and training, appropriate governance of privacy and security, and cross-sectorial collaboration. Common barriers included low user literacy and digital literacy, limited user access to DHT infrastructure, and a lack of policies and protocols to guide the implementation and use of DHTs. CONCLUSIONS The use of DHTs is a viable option to increase equitable access to quality, patient-centered care across Vietnam and simultaneously reduce pressures on the health care system. Vietnam can take advantage of the lessons learned by other low- and middle-income countries in the APR when developing a national road map to digital health transformation. Recommendations that Vietnamese policy makers may consider include emphasizing stakeholder engagement, strengthening digital literacy, supporting the improvement of DHT infrastructure, increasing cross-sectorial collaboration, strengthening governance of cybersecurity, and leading the way in DHT uptake.
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Affiliation(s)
- Leona Kosowicz
- Social Gerontology Division, National Ageing Research Institute, Parkville, Australia
| | - Kham Tran
- Social Gerontology Division, National Ageing Research Institute, Parkville, Australia
| | - Toan Tran Khanh
- Department of Family Medicine, Hanoi Medical University, Hanoi, Vietnam
| | - Thu Ha Dang
- Social Gerontology Division, National Ageing Research Institute, Parkville, Australia
- School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
| | | | - Hue Ta Thi Kim
- New Horizon Palliative Care Company Limited, Hanoi, Vietnam
- Hanoi University of Science and Technology, Hanoi, Vietnam
| | | | | | | | | | - Van Anh Ta
- New Horizon Palliative Care Company Limited, Hanoi, Vietnam
| | - Nilmini Wickramasinghe
- Iverson Health Innovation Research Institute, Swinburne University of Technology, Melbourne, Australia
| | - Penelope Schofield
- School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
| | - John Zelcer
- Iverson Health Innovation Research Institute, Swinburne University of Technology, Melbourne, Australia
| | - Tuan Pham Le
- Department of Family Medicine, Hanoi Medical University, Hanoi, Vietnam
- Military and Civil Medical Association of Vietnam, Hanoi, Vietnam
| | - Tuan Anh Nguyen
- Social Gerontology Division, National Ageing Research Institute, Parkville, Australia
- School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, Australia
- Health Strategy and Policy Institute, Ministry of Health of Vietnam, Hanoi, Vietnam
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Ruyobeza B, Grobbelaar SS, Botha A. Hurdles to developing and scaling remote patients' health management tools and systems: a scoping review. Syst Rev 2022; 11:179. [PMID: 36042505 PMCID: PMC9427160 DOI: 10.1186/s13643-022-02033-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 07/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Despite all the excitement and hype generated regarding the expected transformative impact of digital technology on the healthcare industry, traditional healthcare systems around the world have largely remained unchanged and resultant improvements in developed countries are slower than anticipated. One area which was expected to significantly improve the quality of and access to primary healthcare services in particular is remote patient monitoring and management. Based on a combination of rapid advances in body sensors and information and communication technologies (ICT), it was hoped that remote patient management tools and systems (RPMTSs) would significantly reduce the care burden on traditional healthcare systems as well as health-related costs. However, the uptake or adoption of above systems has been extremely slow and their roll out has not yet properly taken off especially in developing countries where they ought to have made the greatest positive impact. AIM The aim of the study was to assess whether or not recent, relevant literature would support the development of in-community, design, deployment and implementation framework based on three factors thought to be important drivers and levers of RPMTS's adoption and scalability. METHODS A rapid, scoping review conducted on relevant articles obtained from PubMed, MEDLINE, PMC and Cochrane databases and grey literature on Google and published between 2012 and May 2020, by combining a number of relevant search terms and phrases. RESULTS Most RPMTSs are targeted at and focused on a single disease, do not extensively involve patients and clinicians in their early planning and design phases, are not designed to best serve a specific catchment area and are mainly directed at post-hospital, disease management settings. This may be leading to a situation where patients, potential patients and clinicians simply do not make use of these tools, leading to low adoption and scalability thereof. CONCLUSION The development of a user-centred, context-dependent, customizable design and deployment framework could potentially increase the adoption and scalability of RPMTSs, if such framework addressed a combination of diseases, prevalent in a given specific catchment area, especially in developing countries with limited financial resources.
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Affiliation(s)
- Barimwotubiri Ruyobeza
- Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa
| | - Sara S Grobbelaar
- Department of Industrial Engineering, Stellenbosch University, South Africa AND DSI-NRF Centre of Excellence in Scientometrics and Science, Technology and Innovation Policy (SciSTIP), Stellenbosch University, Stellenbosch, South Africa.
| | - Adele Botha
- Department of Industrial Engineering, Stellenbosch University and CSIR Next Generation Enterprises and Institutions, Stellenbosch, South Africa
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Abdulkarem AB, Saud AHM, Abd Allatef MM, Sauod AMA, Abdulkareem MB, Shantaf AM. Internet of Thing for Personalhealthcare Monitoring System. 2022 INTERNATIONAL CONGRESS ON HUMAN-COMPUTER INTERACTION, OPTIMIZATION AND ROBOTIC APPLICATIONS (HORA) 2022. [DOI: 10.1109/hora55278.2022.9800008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Affiliation(s)
| | | | | | | | | | - Ahmed Muhi Shantaf
- Al-Maarif University College,Dept. Computer Engineering Techniques,Ramadi,Iraq
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10
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Char A, Gaudel P, Kulathinal S, Kinnunen TI. Effects of technology-based interventions on dietary intake or anthropometrics among adolescents and adults in South Asia - A systematic review of intervention studies. Obes Res Clin Pract 2022; 16:181-196. [PMID: 35690586 DOI: 10.1016/j.orcp.2022.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 05/19/2022] [Accepted: 06/01/2022] [Indexed: 02/01/2023]
Abstract
INTRODUCTION Mobile technology has been increasingly used as part of dietary interventions, but the effects of such interventions have not been systematically evaluated in the South Asian context. The systematic review aimed to determine the effects of technology-based interventions on dietary intake or anthropometrics among adolescents and adults in South Asia. METHODS Five electronic databases were searched (PubMed, Scopus, Web of Science, Global Health Library and Health Technology Assessment). Studies published in English between 1st January 2011 and 31st December 2021were included. Interventions that evaluated the effects of dietary interventions using technology on dietary outcomes and anthropometrics in adolescents or adults in the age group of 13-44 years (or a broader age group) from South Asia were eligible for inclusion. The risk of bias was assessed using the Cochrane Risk-of-bias 2 tool and ROBINS-I tool. A narrative synthesis was conducted. RESULTS Twenty-one studies met the inclusion criteria (20,667 participants). Eleven of the 17 randomised controlled trials (RCTs) had a high overall risk of bias. The four non-randomised intervention studies had a serious or critical overall risk of bias. When including studies with low risk or some concern for bias, the interventions had a beneficial effect on at least one dietary outcome in four of the six RCTs that measured changes in diet, and no effect on the anthropometric outcomes in the six RCTs that measured changes in anthropometric outcomes. DISCUSSION Technology-based dietary interventions have had some positive effects on dietary intake, but no effects on anthropometry in South Asia. More evidence is needed as the overall risk of bias was high in a majority of the studies.
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Affiliation(s)
- Arundhati Char
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Pramila Gaudel
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Sangita Kulathinal
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Tarja I Kinnunen
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland.
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11
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Lee S, Kim J, Kwon Y, Kim T, Cho S. Privacy Preservation in Patient Information Exchange Systems Based on Blockchain: System Design Study. J Med Internet Res 2022; 24:e29108. [PMID: 35315778 PMCID: PMC8984831 DOI: 10.2196/29108] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/05/2021] [Accepted: 01/17/2022] [Indexed: 11/16/2022] Open
Abstract
Background With the increasing sophistication of the medical industry, various advanced medical services such as medical artificial intelligence, telemedicine, and personalized health care services have emerged. The demand for medical data is also rapidly increasing today because advanced medical services use medical data such as user data and electronic medical records (EMRs) to provide services. As a result, health care institutions and medical practitioners are researching various mechanisms and tools to feed medical data into their systems seamlessly. However, medical data contain sensitive personal information of patients. Therefore, ensuring security while meeting the demand for medical data is a very important problem in the information age for which a solution is required. Objective Our goal is to design a blockchain-based decentralized patient information exchange (PIE) system that can safely and efficiently share EMRs. The proposed system preserves patients’ privacy in the EMRs through a medical information exchange process that includes data encryption and access control. Methods We propose a blockchain-based EMR-sharing system that allows patients to manage their EMRs scattered across multiple hospitals and share them with other users. Our PIE system protects the patient’s EMR from security threats such as counterfeiting and privacy attacks during data sharing. In addition, it provides scalability by using distributed data-sharing methods to quickly share an EMR, regardless of its size or type. We implemented simulation models using Hyperledger Fabric, an open source blockchain framework. Results We performed a simulation of the EMR-sharing process and compared it with previous works on blockchain-based medical systems to check the proposed system’s performance. During the simulation, we found that it takes an average of 0.01014 (SD 0.0028) seconds to download 1 MB of EMR in our proposed PIE system. Moreover, it has been confirmed that data can be freely shared with other users regardless of the size or format of the data to be transmitted through the distributed data-sharing technique using the InterPlanetary File System. We conducted a security analysis to check whether the proposed security mechanism can effectively protect users of the EMR-sharing system from security threats such as data forgery or unauthorized access, and we found that the distributed ledger structure and re-encryption–based data encryption method can effectively protect users’ EMRs from forgery and privacy leak threats and provide data integrity. Conclusions Blockchain is a distributed ledger technology that provides data integrity to enable patient-centered health information exchange and access control. PIE systems integrate and manage fragmented patient EMRs through blockchain and protect users from security threats during the data exchange process among users. To increase safety and efficiency in the EMR-sharing process, we used access control using security levels, data encryption based on re-encryption, and a distributed data-sharing scheme.
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Affiliation(s)
- Sejong Lee
- Department of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea.,Major in Bio-Artificial Intelligence, Hanyang University, Ansan, Republic of Korea
| | - Jaehyeon Kim
- Major in Bio-Artificial Intelligence, Hanyang University, Ansan, Republic of Korea.,Department of Applied Artificial Intelligence, Hanyang University, Ansan, Republic of Korea
| | - Yongseok Kwon
- Department of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea.,Major in Bio-Artificial Intelligence, Hanyang University, Ansan, Republic of Korea
| | - Teasung Kim
- Department of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea
| | - Sunghyun Cho
- Department of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea
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12
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Lamb JJ, Stone M, D’Adamo CR, Volkov A, Metti D, Aronica L, Minich D, Leary M, Class M, Carullo M, Ryan JJ, Larson IA, Lundquist E, Contractor N, Eck B, Ordovas JM, Bland JS. Personalized Lifestyle Intervention and Functional Evaluation Health Outcomes SurvEy: Presentation of the LIFEHOUSE Study Using N-of-One Tent-Umbrella-Bucket Design. J Pers Med 2022; 12:115. [PMID: 35055430 PMCID: PMC8779079 DOI: 10.3390/jpm12010115] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/31/2021] [Accepted: 01/11/2022] [Indexed: 12/20/2022] Open
Abstract
The working definition of health is often the simple absence of diagnosed disease. This common standard is limiting given that changes in functional health status represent early warning signs of impending health declines. Longitudinal assessment of functional health status may foster prevention of disease occurrence and modify disease progression. The LIFEHOUSE (Lifestyle Intervention and Functional Evaluation-Health Outcomes SurvEy) longitudinal research project explores the impact of personalized lifestyle medicine approaches on functional health determinants. Utilizing an adaptive tent-umbrella-bucket design, the LIFEHOUSE study follows the functional health outcomes of adult participants recruited from a self-insured employee population. Participants were each allocated to the tent of an all-inclusive N-of-one case series. After assessing medical history, nutritional physical exam, baseline functional status (utilizing validated tools to measure metabolic, physical, cognitive, emotional and behavioral functional capacity), serum biomarkers, and genomic and microbiome markers, participants were assigned to applicable umbrellas and buckets. Personalized health programs were developed and implemented using systems biology formalism and functional medicine clinical approaches. The comprehensive database (currently 369 analyzable participants) will yield novel interdisciplinary big-health data and facilitate topological analyses focusing on the interactome among each participant's genomics, microbiome, diet, lifestyle and environment.
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Affiliation(s)
- Joseph J. Lamb
- Personalized Lifestyle Medicine Center, Gig Harbor, WA 98332, USA; (M.S.); (D.M.)
| | - Michael Stone
- Personalized Lifestyle Medicine Center, Gig Harbor, WA 98332, USA; (M.S.); (D.M.)
- Office of Personalized Health and Well-Being, Medical College of Georgia, AU/UGA Medical Partnership, Athens, GA 30606, USA
- Institute for Functional Medicine, Federal Way, WA 98003, USA; (C.R.D.); (D.M.); (M.C.)
| | - Christopher R. D’Adamo
- Institute for Functional Medicine, Federal Way, WA 98003, USA; (C.R.D.); (D.M.); (M.C.)
- Center for Integrative Medicine, University of Maryland, Baltimore, MD 21201, USA
| | | | - Dina Metti
- Personalized Lifestyle Medicine Center, Gig Harbor, WA 98332, USA; (M.S.); (D.M.)
| | - Lucia Aronica
- Metagenics, Inc., Aliso Viejo, CA 92656, USA; (L.A.); (M.C.); (I.A.L.); (N.C.); (B.E.)
- Department of Medicine, Stanford Prevention Research Center, Stanford University, Stanford, CA 94305, USA
| | - Deanna Minich
- Institute for Functional Medicine, Federal Way, WA 98003, USA; (C.R.D.); (D.M.); (M.C.)
- Human Nutrition and Functional Medicine, University of Western States, Portland, OR 97213, USA
| | | | - Monique Class
- Institute for Functional Medicine, Federal Way, WA 98003, USA; (C.R.D.); (D.M.); (M.C.)
- The Center for Functional Medicine, Stamford, CT 06905, USA
| | - Malisa Carullo
- Metagenics, Inc., Aliso Viejo, CA 92656, USA; (L.A.); (M.C.); (I.A.L.); (N.C.); (B.E.)
| | - Jennifer J. Ryan
- Helfgott Research Institute, National University of Natural Medicine, Portland, OR 97201, USA;
| | - Ilona A. Larson
- Metagenics, Inc., Aliso Viejo, CA 92656, USA; (L.A.); (M.C.); (I.A.L.); (N.C.); (B.E.)
| | - Erik Lundquist
- Personalized Lifestyle Medicine Center, Aliso Viejo, CA 92656, USA;
| | - Nikhat Contractor
- Metagenics, Inc., Aliso Viejo, CA 92656, USA; (L.A.); (M.C.); (I.A.L.); (N.C.); (B.E.)
| | - Brent Eck
- Metagenics, Inc., Aliso Viejo, CA 92656, USA; (L.A.); (M.C.); (I.A.L.); (N.C.); (B.E.)
| | - Jose M. Ordovas
- Jean Meyer USDA Human Nutrition Center on Aging, Tufts University, Boston, MA 02111, USA;
| | - Jeffrey S. Bland
- Personalized Lifestyle Medicine Institute, Bainbridge Island, WA 98110, USA;
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13
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Abstract
Sustainable technologies are being increasingly used in various areas of human life. While they have a multitude of benefits, they are especially useful in health monitoring, especially for certain groups of people, such as the elderly. However, there are still several issues that need to be addressed before its use becomes widespread. This work aims to clarify the aspects that are of great importance for increasing the acceptance of the use of this type of technology in the elderly. In addition, we aim to clarify whether the technologies that are already available are able to ensure acceptable accuracy and whether they could replace some of the manual approaches that are currently being used. A two-week study with people 65 years of age and over was conducted to address the questions posed here, and the results were evaluated. It was demonstrated that simplicity of use and automatic functioning play a crucial role. It was also concluded that technology cannot yet completely replace traditional methods such as questionnaires in some areas. Although the technologies that were tested were classified as being “easy to use”, the elderly population in the current study indicated that they were not sure that they would use these technologies regularly in the long term because the added value is not always clear, among other issues. Therefore, awareness-raising must take place in parallel with the development of technologies and services.
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14
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Martyushev-Poklad A, Yankevich D. Patent Landscape of Automated Systems for Personalized Health Management (ASHM): Features, Shortcomings, and Implications for Developing an Optimal ASHM. Front Digit Health 2021; 3:579936. [PMID: 34713081 PMCID: PMC8522012 DOI: 10.3389/fdgth.2021.579936] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 01/26/2021] [Indexed: 11/15/2022] Open
Abstract
The current struggle of national health care systems against global epidemic of non-communicable diseases (NCD) is both clinically ineffective and cost ineffective. On the other hand, rapid development of systems biology, P4 medicine and new digital and communication technologies are good prerequisites for creating an affordable and scalable automated system for personalized health management (ASHM). The current practice of ASHM is better represented in patent literature (36 relevant documents found in Google Patents and USPTO) than in scientific papers (17 documents found in PubMed and Google Scholar). However, only a small fraction of publications disclose a complete self-sufficient system. Problems that authors of ASHM aim to address, methodological approaches, and the most important technical solutions are reviewed and discussed along with shortcomings and limitations. Technical solutions for ASHM currently commercialized or described in literature generally fail to enable practicable, scalable and affordable automated and individualized screening, monitoring, prevention and correction of human health conditions. They also fail to provide a decision support system to patients that would help effectively prevent major NCD and their complications, be accessible and cost effective, consider individual lifestyle factors and involve patients in management of their individual health. Based on analysis of the literature, models of health and care, we propose conceptual framework for developing an ASHM that would be free from the mentioned problems.
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Affiliation(s)
- Andrey Martyushev-Poklad
- Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russia
| | - Dmitry Yankevich
- Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russia
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15
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Viana JN, Edney S, Gondalia S, Mauch C, Sellak H, O'Callaghan N, Ryan JC. Trends and gaps in precision health research: a scoping review. BMJ Open 2021; 11:e056938. [PMID: 34697128 PMCID: PMC8547511 DOI: 10.1136/bmjopen-2021-056938] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 10/08/2021] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVE To determine progress and gaps in global precision health research, examining whether precision health studies integrate multiple types of information for health promotion or restoration. DESIGN Scoping review. DATA SOURCES Searches in Medline (OVID), PsycINFO (OVID), Embase, Scopus, Web of Science and grey literature (Google Scholar) were carried out in June 2020. ELIGIBILITY CRITERIA Studies should describe original precision health research; involve human participants, datasets or samples; and collect health-related information. Reviews, editorial articles, conference abstracts or posters, dissertations and articles not published in English were excluded. DATA EXTRACTION AND SYNTHESIS The following data were extracted in independent duplicate: author details, study objectives, technology developed, study design, health conditions addressed, precision health focus, data collected for personalisation, participant characteristics and sentence defining 'precision health'. Quantitative and qualitative data were summarised narratively in text and presented in tables and graphs. RESULTS After screening 8053 articles, 225 studies were reviewed. Almost half (105/225, 46.7%) of the studies focused on developing an intervention, primarily digital health promotion tools (80/225, 35.6%). Only 28.9% (65/225) of the studies used at least four types of participant data for tailoring, with personalisation usually based on behavioural (108/225, 48%), sociodemographic (100/225, 44.4%) and/or clinical (98/225, 43.6%) information. Participant median age was 48 years old (IQR 28-61), and the top three health conditions addressed were metabolic disorders (35/225, 15.6%), cardiovascular disease (29/225, 12.9%) and cancer (26/225, 11.6%). Only 68% of the studies (153/225) reported participants' gender, 38.7% (87/225) provided participants' race/ethnicity, and 20.4% (46/225) included people from socioeconomically disadvantaged backgrounds. More than 57% of the articles (130/225) have authors from only one discipline. CONCLUSIONS Although there is a growing number of precision health studies that test or develop interventions, there is a significant gap in the integration of multiple data types, systematic intervention assessment using randomised controlled trials and reporting of participant gender and ethnicity. Greater interdisciplinary collaboration is needed to gather multiple data types; collectively analyse big and complex data; and provide interventions that restore, maintain and/or promote good health for all, from birth to old age.
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Affiliation(s)
- John Noel Viana
- Responsible Innovation Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia
- Australian National Centre for the Public Awareness of Science, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Sarah Edney
- Physical Activity and Nutrition Determinants in Asia (PANDA) programme, Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Shakuntla Gondalia
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Chelsea Mauch
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Hamza Sellak
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Data61, Commonwealth Scientific and Industrial Research Organisation, Melbourne, Victoria, Australia
| | - Nathan O'Callaghan
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Jillian C Ryan
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
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16
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Slevin P, Kessie T, Cullen J, Butler MW, Donnelly SC, Caulfield B. A qualitative study of clinician perceptions regarding the potential role for digital health interventions for the management of COPD. Health Informatics J 2021; 27:1460458221994888. [PMID: 33653189 DOI: 10.1177/1460458221994888] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Effective self-management of chronic obstructive pulmonary disease (COPD) can lead to increased patient control and reduced health care costs. However, both patients and healthcare professionals encounter significant challenges. Digital health interventions, such as smart oximeters and COPD self-management applications, promise to enhance the management of COPD, yet, there is little evidence to support their use and user-experience issues are still common. Understanding the needs of healthcare professionals is central for increasing adoption and engagement with digital health interventions but little is known about their perceptions of digital health interventions in COPD. This paper explored the perceptions of healthcare professionals regarding the potential role for DHI in the management of COPD. Snowball sampling was used to recruit the participants (n = 32). Each participant underwent a semi-structured interview. Using NVivo 12 software, thematic analysis was completed. Healthcare professionals perceive digital health interventions providing several potential benefits to the management of COPD including the capture of patient status indicators during the interappointment period, providing new patient data to support the consultation process and perceived digital health interventions as a potential means to improve patient engagement. The findings offer new insights regarding potential future use-cases for digital health interventions in COPD, which can help ease user-experience issues as they align with the needs of healthcare professionals.
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Affiliation(s)
| | | | - John Cullen
- Tallaght University Hospital, Ireland.,Trinity College Dublin, Ireland
| | - Marcus W Butler
- University College Dublin, Ireland.,St. Vincent's University Hospital, Ireland
| | - Seamas C Donnelly
- Tallaght University Hospital, Ireland.,Trinity College Dublin, Ireland
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17
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Cui M, Baek SS, Crespo RG, Premalatha R. Internet of things-based cloud computing platform for analyzing the physical health condition. Technol Health Care 2021; 29:1233-1247. [PMID: 34092673 DOI: 10.3233/thc-213003] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Health monitoring is important for early disease diagnosis and will reduce the discomfort and treatment expenses, which is very relevant in terms of prevention. The early diagnosis and treatment of multiple conditions will improve solutions to the patient's healthcare radically. A concept model for the real-time patient tracking system is the primary goal of the method. The Internet of things (IoT) has made health systems accessible for programs based on the value of patient health. OBJECTIVE In this paper, the IoT-based cloud computing for patient health monitoring framework (IoT-CCPHM), has been proposed for effective monitoring of the patients. METHOD The emerging connected sensors and IoT devices monitor and test the cardiac speed, oxygen saturation percentage, body temperature, and patient's eye movement. The collected data are used in the cloud database to evaluate the patient's health, and the effects of all measures are stored. The IoT-CCPHM maintains that the medical record is processed in the cloud servers. RESULTS The experimental results show that patient health monitoring is a reliable way to improve health effectively.
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Affiliation(s)
- Mengyao Cui
- Yangtze Normal University, Chongqing, China.,Sangmyung University, Seoul, Korea
| | | | - Rubén González Crespo
- Computer Science Department, School of Engineering and Technology, Universidad Internacional de La Rioja, Spain
| | - R Premalatha
- Department of Computer Science, IFET College of Engineering, India
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18
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Koteluk O, Wartecki A, Mazurek S, Kołodziejczak I, Mackiewicz A. How Do Machines Learn? Artificial Intelligence as a New Era in Medicine. J Pers Med 2021; 11:jpm11010032. [PMID: 33430240 PMCID: PMC7825660 DOI: 10.3390/jpm11010032] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 12/31/2020] [Accepted: 01/05/2021] [Indexed: 02/06/2023] Open
Abstract
With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to make faster and more correct decisions and improving current standards of treatment. Today, machines can analyze, learn, communicate, and understand processed data and are used in health care increasingly. This review explains different models and the general process of machine learning and training the algorithms. Furthermore, it summarizes the most useful machine learning applications and tools in different branches of medicine and health care (radiology, pathology, pharmacology, infectious diseases, personalized decision making, and many others). The review also addresses the futuristic prospects and threats of applying artificial intelligence as an advanced, automated medicine tool.
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Affiliation(s)
- Oliwia Koteluk
- Faculty of Medical Sciences, Chair of Medical Biotechnology, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (O.K.); (A.W.)
| | - Adrian Wartecki
- Faculty of Medical Sciences, Chair of Medical Biotechnology, Poznan University of Medical Sciences, 61-701 Poznan, Poland; (O.K.); (A.W.)
| | - Sylwia Mazurek
- Department of Cancer Immunology, Chair of Medical Biotechnology, Poznan University of Medical Sciences, 61-701 Poznan, Poland;
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Centre, 61-866 Poznan, Poland
- Correspondence: ; Tel.: +48-61-885-06-67
| | - Iga Kołodziejczak
- Postgraduate School of Molecular Medicine, Medical University of Warsaw, 02-091 Warsaw, Poland;
| | - Andrzej Mackiewicz
- Department of Cancer Immunology, Chair of Medical Biotechnology, Poznan University of Medical Sciences, 61-701 Poznan, Poland;
- Department of Cancer Diagnostics and Immunology, Greater Poland Cancer Centre, 61-866 Poznan, Poland
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19
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Shiferaw KB, Tilahun BC, Endehabtu BF, Gullslett MK, Mengiste SA. E-health literacy and associated factors among chronic patients in a low-income country: a cross-sectional survey. BMC Med Inform Decis Mak 2020; 20:181. [PMID: 32762745 PMCID: PMC7407428 DOI: 10.1186/s12911-020-01202-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 07/23/2020] [Indexed: 02/03/2023] Open
Abstract
Background Chronic patients persistently seek for health information on the internet for medication information seeking, nutrition, disease management, information regarding disease preventive actions and so on. Consumers ability to search, find, appraise and use health information from the internet is known as eHealth literacy skill. eHealth literacy is a congregate set of six basic skills (traditional literacy, health literacy, information literacy, scientific literacy, media literacy and computer literacy). The aim of this study was to assess eHealth literacy level and associated factors among internet user chronic patients in North-west Ethiopia. Methods Institutional based cross-sectional study design was conducted. Stratified sampling technique was used to select 423 study participants among chronic patients. The eHealth literacy scale (eHEALS) was used for data collection. The eHEALS is a validated eight-item Likert scaled questionnaire used to asses self-reported capability of eHealth consumers to find, appraise, and use health related information from the internet to solve health problems. Statistical Package for Social science version 20 was used for data entry and further analysis. Multivariable logistic regression was used to examine the association between the eHealth literacy skill and associated factors. Significance was obtained at 95% CI and p < 0.05. Result In total, 423 study subjects were approached and included in the study from February to May, 2019. The response rate to the survey was 95.3%. The majority of respondents 268 (66.3%) were males and mean age was 35.58 ± 14.8 years. The multivariable logistic regression model indicated that participants with higher education (at least having the diploma) are more likely to possess high eHealth literacy skill with Adjusted Odds Ratio (AOR): 3.48, 95% CI (1.54, 7.87). similarly, being government employee AOR: 1.71, 95% CI (1.11, 2.68), being urban resident AOR: 1.37, 95% CI (0.54, 3.49), perceived good health status AOR: 3.97, 95% CI (1.38, 11.38), having higher income AOR: 4.44, 95% CI (1.32, 14.86), Daily internet use AOR: 2.96, 95% CI (1.08, 6.76), having good knowledge about the availability and importance of online resources AOR: 3.12, 95% CI (1.61, 5.3), having positive attitude toward online resources AOR: 2.94, 95% CI (1.07, 3.52) and higher level of computer literacy AOR: 3.81, 95% CI (2.19, 6.61) were the predictors positively associated with higher eHealth literacy level. Conclusion Besides the mounting indication of efficacy, the present data confirm that internet use and eHealth literacy level of chronic patients in this setting is relatively low which clearly implicate that there is a need to fill the skill gap in eHealth literacy among chronic patients which might help them in finding and evaluating relevant online sources for their health-related decisions.
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Affiliation(s)
- Kirubel Biruk Shiferaw
- Health Informatics Department, Medicine and Health science college, Debre Markos University, Debre Markos, Ethiopia.
| | - Binyam Chakilu Tilahun
- Health Informatics Department, College of Medicine and Health science, University of Gondar, Gondar, Ethiopia
| | - Berhanu Fikadie Endehabtu
- Health Informatics Department, College of Medicine and Health science, University of Gondar, Gondar, Ethiopia
| | - Monika Knudsen Gullslett
- Faculty of Health & Social Sciences, Science center Health & Technology, University of South-Eastern Norway, Notodden, Norway
| | - Shegaw Anagaw Mengiste
- School of Business, Institute of Business, History & Social Sciences, University of South-Eastern Norway, Notodden, Norway
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20
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Benedetto S, Caldato C, Greenwood DC, Bartoli N, Pensabene V, Actis P. Remote heart rate monitoring - Assessment of the Facereader rPPg by Noldus. PLoS One 2019; 14:e0225592. [PMID: 31756239 PMCID: PMC6874325 DOI: 10.1371/journal.pone.0225592] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 10/23/2019] [Indexed: 11/18/2022] Open
Abstract
Remote photoplethysmography (rPPG) allows contactless monitoring of human cardiac activity through a video camera. In this study, we assessed the accuracy and precision for heart rate measurements of the only consumer product available on the market, namely the FacereaderTM rPPG by Noldus, with respect to a gold standard electrocardiograph. Twenty-four healthy participants were asked to sit in front of a computer screen and alternate two periods of rest with two stress tests (i.e. Go/No-Go task), while their heart rate was simultaneously acquired for 20 minutes using the ECG criterion measure and the FacereaderTM rPPG. Results show that the FacereaderTM rPPG tends to overestimate lower heart rates and underestimate higher heart rates compared to the ECG. The Facereader™ rPPG revealed a mean bias of 9.8 bpm, the 95% limits of agreement (LoA) ranged from almost -30 up to +50 bpm. These results suggest that whilst the rPPG FacereaderTM technology has potential for contactless heart rate monitoring, its predictions are inaccurate for higher heart rates, with unacceptable precision across the entire range, rendering its estimates unreliable for monitoring individuals.
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Affiliation(s)
| | | | - Darren C. Greenwood
- Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
- Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom
| | | | - Virginia Pensabene
- School of Electronic and Electrical Engineering, University of Leeds, Leeds, West Yorkshire, United Kingdom
- School of Medicine, Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, West Yorkshire, United Kingdom
| | - Paolo Actis
- School of Electronic and Electrical Engineering, University of Leeds, Leeds, West Yorkshire, United Kingdom
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21
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Malekian Borujeni A, Fathy M, Mozayani N. A hierarchical, scalable architecture for a real-time monitoring system for an electrocardiography, using context-aware computing. J Biomed Inform 2019; 96:103251. [PMID: 31326625 DOI: 10.1016/j.jbi.2019.103251] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 07/05/2019] [Accepted: 07/12/2019] [Indexed: 11/29/2022]
Abstract
Heart failure is one of the most common cause of death in the world. The real-time health monitoring system with the advent of the Internet of things has attracted growing attention in the health care industry, which can help reducing the death rate of heart failure. Despite the recent success of these efforts, there have been some limitations, such as response time, scalability, latency and fault tolerance. To address these issues, in this paper, we propose a hierarchical architecture with four layers to develop health care systems. In the proposed model, the vital signs of a patient are measured by means of a body sensor network and sent to a smart health care system. Each of these layers is related to a certain level of heart failure. Therefore, in the proposed model, simple and low-risk heart failure can be detected quickly before it reaches to a dangerous level. Empirical results confirm a significant improvement in terms of response time and scalability in comparison with the state of the art techniques.
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Affiliation(s)
| | - Mahmood Fathy
- Iran University of Science and Technology, Tehran, Iran.
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22
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Construction of medical equipment-based doctor health monitoring system. J Med Syst 2019; 43:138. [PMID: 30969376 PMCID: PMC6458979 DOI: 10.1007/s10916-019-1255-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 03/27/2019] [Indexed: 11/02/2022]
Abstract
The health status of doctors has been overlooked by the society and even the doctors themselves, especially those doctors who work long hours. Their attention is always on patients, so they are more likely to ignore their own health problems. Therefore, in this paper, we propose a medical equipment-based doctor health monitoring system (hereinafter referred to as Doc-care). Doc-care can be used as a private health manager for doctors, and doctors can monitor their health indicators in real time while using medical equipment to aid diagnosis and treatment. When the doctor's health status is neglected, Doc-care can protect the doctor's health; combining with the convolutional neural network method to detect and grade the doctor's health indicators, to assess the doctor's real-time health status. After referring to the doctor's past health data in the cloud server, giving appropriate advice and predictions about the doctor's health status.
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Hou J, Yang R, Yang Y, Tang Y, Deng H, Chen Z, Wu Y, Shen H. The Effectiveness and Safety of Utilizing Mobile Phone-Based Programs for Rehabilitation After Lumbar Spinal Surgery: Multicenter, Prospective Randomized Controlled Trial. JMIR Mhealth Uhealth 2019; 7:e10201. [PMID: 30785406 PMCID: PMC6404639 DOI: 10.2196/10201] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Revised: 11/01/2018] [Accepted: 12/08/2018] [Indexed: 01/12/2023] Open
Abstract
Background Rehabilitation is crucial for postoperative patients with low back pain (LBP). However, the implementation of traditional clinic-based programs is limited in developing countries, such as China, because of the maldistribution of medical resources. Mobile phone–based programs may be a potential substitute for those who have no access to traditional rehabilitation. Objective The aim of this study was to examine the efficacy of mobile phone–based rehabilitation systems in patients who underwent lumbar spinal surgery. Methods Patients who accepted spinal surgeries were recruited and randomized into 2 groups of rehabilitation treatments: (1) a mobile phone–based eHealth (electronic health) program (EH) or (2) usual care treatment (UC). The primary outcomes were (1) function and pain status assessed by the Oswestry Disability Index (ODI) and (2) the visual analog scale (VAS). Secondary outcomes were (1) general mental health and (2) quality of life (Likert scales, EuroQol-5 Dimension health questionnaire, and 36-item Short-Form Health Survey). All the patients were assessed preoperatively and then at 3, 6, 12, and 24 months postoperatively. Results A total of 168 of the 863 eligible patients were included and randomized in this study. Our analysis showed that the improvement of primary outcomes in the EH group was superior to the UC group at 24 months postoperatively (ODI mean 7.02, SD 3.10, P<.05; VAS mean 7.59, SD 3.42, P<.05). No significant difference of primary outcomes was found at other time points. A subgroup analysis showed that the improvements of the primary outcomes were more significant in those who completed 6 or more training sessions each week throughout the trial (the highest compliance group) compared with the UC group at 6 months (ODI mean 17.94, SD 5.24, P<.05; VAS mean 19.56, SD 5.27, P<.05), 12 months (ODI mean 13.39, SD 5.32, P<.05; VAS mean 14.35, SD 5.23, P<.05), and 24 months (ODI mean 18.80, SD 5.22, P<.05; VAS mean 21.56, SD 5.28, P<.05). Conclusions This research demonstrated that a mobile phone–based telerehabilitation system is effective in self-managed rehabilitation for postoperative patients with LBP. The effectiveness of eHealth was more evident in participants with higher compliance. Future research should focus on improving patients’ compliance. Trial Registration Chinese Clinical Trial Registry ChiCTR-TRC-13003314; http://www.chictr.org.cn/showproj.aspx?proj=6245 (Archived by WebCite at http://www.webcitation.org/766RAIDNc)
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Affiliation(s)
- Jingyi Hou
- Department of Orthopedics, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Rui Yang
- Department of Orthopedics, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yaping Yang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yiyong Tang
- Department of Orthopedics, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Haiquan Deng
- Department of Orthopedics, Guangxi Region People's Hospital, Nanning, China
| | - Zhong Chen
- Department of Orthopedics, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yanfeng Wu
- Department of Biotherapy Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huiyong Shen
- Department of Orthopedics, 8th Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, China
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Malembaka EB, Karemere H, Balaluka GB, Lambert AS, Muneza F, Deconinck H, Macq J. A new look at population health through the lenses of cognitive, functional and social disability clustering in eastern DR Congo: a community-based cross-sectional study. BMC Public Health 2019; 19:93. [PMID: 30665386 PMCID: PMC6341676 DOI: 10.1186/s12889-019-6431-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 01/11/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The importance of viewing health from a broader perspective than the mere presence or absence of disease is critical at primary healthcare level. However, there is scanty evidence-based stratification of population health using other criteria than morbidity-related indicators in developing countries. We propose a novel stratification of population health based on cognitive, functional and social disability and its covariates at primary healthcare level in DR Congo. METHOD We conducted a community-based cross-sectional study in adults with diabetes or hypertension, mother-infant pairs with child malnutrition, their informal caregivers and randomly selected neighbours in rural and sub-urban health zones in South-Kivu Province, DR Congo. We used the WHO Disability Assessment Schedule 2.0 (WHODAS) to measure functional, cognitive and social disability. The study outcome was health status clustering derived from a principal component analysis with hierarchical clustering around the WHODAS domains scores. We calculated adjusted odds ratios (AOR) using mixed-effects ordinal logistic regression. RESULTS Of the 1609 respondents, 1266 had WHODAS data and an average age of 48.3 (SD: 18.7) years. Three hierarchical clusters were identified: 9.2% of the respondents were in cluster 3 of high dependency, 21.1% in cluster 2 of moderate dependency and 69.7% in cluster 1 of minor dependency. Associated factors with higher disability clustering were being a patient compared to being a neighbour (AOR: 3.44; 95% CI: 1.93-6.15), residency in rural Walungu health zone compared to semi-urban Bagira health zone (4.67; 2.07-10.58), female (2.1; 1.25-2.94), older (1.05; 1.04-1.07), poorest (2.60; 1.22-5.56), having had an acute illness 30 days prior to the interview (2.11; 1.24-3.58), and presenting with either diabetes or hypertension (2.73; 1.64-4.53) or both (6.37; 2.67-15.17). Factors associated with lower disability clustering were being informally employed (0.36; 0.17-0.78) or a petty trader/farmer (0.44; 0.22-0.85). CONCLUSION Health clustering derived from WHODAS domains has the potential to suitably classify individuals based on the level of health needs and dependency. It may be a powerful lever for targeting appropriate healthcare service provision and setting priorities based on vulnerability rather than solely presence of disease.
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Affiliation(s)
- Espoir Bwenge Malembaka
- Ecole Régionale de Santé Publique, ERSP, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo
- Institute of Health and Society, IRSS, Université Catholique de Louvain, Brussels, Belgium
| | - Hermès Karemere
- Ecole Régionale de Santé Publique, ERSP, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo
| | - Ghislain Bisimwa Balaluka
- Ecole Régionale de Santé Publique, ERSP, Faculté de Médecine, Université Catholique de Bukavu, Bukavu, Democratic Republic of Congo
| | - Anne-Sophie Lambert
- Institute of Health and Society, IRSS, Université Catholique de Louvain, Brussels, Belgium
| | - Fiston Muneza
- Department of Epidemiology and Biostatics, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Hedwig Deconinck
- Institute of Health and Society, IRSS, Université Catholique de Louvain, Brussels, Belgium
| | - Jean Macq
- Institute of Health and Society, IRSS, Université Catholique de Louvain, Brussels, Belgium
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“Technology enabled Health” – Insights from twitter analytics with a socio-technical perspective. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT 2018. [DOI: 10.1016/j.ijinfomgt.2018.07.003] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Pathinarupothi RK, Rangan ES, Durga P. Deriving High Performance Alerts from Reduced Sensor Data for Timely Intervention in Acute Hypotensive Episodes. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:3260-3263. [PMID: 30441087 DOI: 10.1109/embc.2018.8512945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Alerting critical health conditions ahead of time leads to reduced mortality rates. Recently wirelessly enabled medical sensors have become pervasive in both hospital and ambulatory settings. These sensors pour out voluminous data that are generally not amenable to direct interpretation. For this data to be practically useful for patients, they must be translatable into alerts that enable doctors to intervene in a timely fashion. In this paper we present a novel three-step technique to derive high performance alerts from voluminous sensor data: A data reduction algorithm that takes into account the medical condition at personalized patient level and thereby converts raw multi-sensor data to patient and disease specific severity representation, which we call as the Personalized Health Motifs (PHM). The PHMs are then modulated by criticality factors derived from interventional time and severity frequency to yield a Criticality Measure Index (CMI). In the final step we generate alerts whenever the CMI crosses patientdisease-specific thresholds. We consider one medical condition called Acute Hypotensive Episode (AHE). We evaluate the performance of our CMI derived alerts using 7,200 minutes of data from the MIMIC II [7] database. We show that the CMI generates valid alerts up to 180 minutes prior to onset of AHE with accuracy, specificity, and sensitivity of 0.76, 1.0 and 0.67 respectively, outperforming alerts from raw data.
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Nedungadi P, Iyer A, Gutjahr G, Bhaskar J, Pillai AB. Data-Driven Methods for Advancing Precision Oncology. CURRENT PHARMACOLOGY REPORTS 2018; 4:145-156. [PMID: 33520605 PMCID: PMC7845924 DOI: 10.1007/s40495-018-0127-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
PURPOSE OF REVIEW This article discusses the advances, methods, challenges, and future directions of data-driven methods in advancing precision oncology for biomedical research, drug discovery, clinical research, and practice. RECENT FINDINGS Precision oncology provides individually tailored cancer treatment by considering an individual's genetic makeup, clinical, environmental, social, and lifestyle information. Challenges include voluminous, heterogeneous, and disparate data generated by different technologies with multiple modalities such as Omics, electronic health records, clinical registries and repositories, medical imaging, demographics, wearables, and sensors. Statistical and machine learning methods have been continuously adapting to the ever-increasing size and complexity of data. Precision Oncology supportive analytics have improved turnaround time in biomarker discovery and time-to-application of new and repurposed drugs. Precision oncology additionally seeks to identify target patient populations based on genomic alterations that are sensitive or resistant to conventional or experimental treatments. Predictive models have been developed for cancer progression and survivorship, drug sensitivity and resistance, and identification of the most suitable combination treatments for individual patient scenarios. In the future, clinical decision support systems need to be revamped to better incorporate knowledge from precision oncology, thus enabling clinical practitioners to provide precision cancer care. SUMMARY Open Omics datasets, machine learning algorithms, and predictive models have enabled the advancement of precision oncology. Clinical decision support systems with integrated electronic health record and Omics data are needed to provide data-driven recommendations to assist clinicians in disease prevention, early identification, and individualized treatment. Additionally, as cancer is a constantly evolving disorder, clinical decision systems will need to be continually updated based on more recent knowledge and datasets.
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Affiliation(s)
- Prema Nedungadi
- Center for Research in Analytics & Technology in Education, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India
- Department of Computer Science, School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India
| | - Akshay Iyer
- Center for Research in Analytics & Technology in Education, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India
| | - Georg Gutjahr
- Center for Research in Analytics & Technology in Education, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India
| | - Jasmine Bhaskar
- Center for Research in Analytics & Technology in Education, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India
- Department of Computer Science, School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, India
| | - Asha B. Pillai
- Division of Pediatric Hematology/Oncology, Departments of Pediatrics and Microbiology and Immunology, University of Miami Miller School of Medicine, Miami, FL, USA
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