Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible t...Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible to cybersecurity threats due to its reliance on low-power biomedical devices and the use of open wireless channels for communication.In this article,we intend to address this shortcoming,and as a result,we propose a new scheme called,the certificateless anonymous authentication(CAA)scheme.The proposed scheme is based on hyperelliptic curve cryptography(HECC),an enhanced variant of elliptic curve cryptography(ECC)that employs a smaller key size of 80 bits as compared to 160 bits.The proposed scheme is secure against various attacks in both formal and informal security analyses.The formal study makes use of the Real-or-Random(ROR)model.A thorough comparative study of the proposed scheme is conducted for the security and efficiency of the proposed scheme with the relevant existing schemes.The results demonstrate that the proposed scheme not only ensures high security for health-related data but also increases efficiency.The proposed scheme’s computation cost is 2.88 ms,and the communication cost is 1440 bits,which shows its better efficiency compared to its counterpart schemes.展开更多
Falling is among the most harmful events older adults may encounter.With the continuous growth of the aging population in many societies,developing effective fall detection mechanisms empowered by machine learning tec...Falling is among the most harmful events older adults may encounter.With the continuous growth of the aging population in many societies,developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes essential.This paper presents a new healthcare Internet of Health Things(IoHT)architecture built around an ensemble machine learning-based fall detection system(FDS)for older people.Compared to deep neural networks,the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal hyperparameters.The number of cascaded random forest stages is automatically optimized.This study uses a public dataset of fall detection samples called SmartFall to validate the developed fall detection system.The SmartFall dataset is collected based on the acquired measurements of the three-axis accelerometer in a smartwatch.Each scenario in this dataset is classified and labeled as a fall or a non-fall.In comparison to the three machine learning models—K-nearest neighbors(KNN),decision tree(DT),and standard random forest(SRF),the proposed ensemble classifier outperformed the other models and achieved 98.4%accuracy.The developed healthcare IoHT framework can be realized for detecting fall accidents of older people by taking security and privacy concerns into account in future work.展开更多
Objective:To observe the status quo of patients’psychological distress,and to explore the effect of Internet+health education model(IHEM)on patients who experienced psychological distress during their first hemodialy...Objective:To observe the status quo of patients’psychological distress,and to explore the effect of Internet+health education model(IHEM)on patients who experienced psychological distress during their first hemodialysis treatment,with the goal of reducing their psychological distress and improving their quality of life.Methods:IHEM was conducted on 120 first-time hemodialysis patients for 3 months while a distress thermometer and a list of questionnaires were used to screen patients and provide corresponding psychological intervention.The incidence rate of psychological distress was analyzed statistically to explore the difference in psychological distress at various periods.Results:The incidence rate(score≥4)of psychological distress in first-time hemodialysis patients was 46.67%,and their distress was mainly rooted in physical,emotional,practical problems(economy,time,and energy),etc.Through IHEM,the psychological distress scores of the patients decreased to 3.29±1.02 at one month after their discharge,and the incidence rate was 32.14%;the psychological distress scores of the patients were 2.29±1.02 at 3 months after their discharge,and the incidence rate was 21.14%.The difference before and after the intervention was statistically significant(P<0.05).Conclusion:A psychological distress thermometer can timely detect the degree and causes of psychological distress among first-time hemodialysis patients,and the use of IHEM may significantly alleviate the psychological distress among hemodialysis patients.展开更多
The Internet of things has particularly novel implications in the area of public health. This is due to (1) The rapid and widespread adoption of powerful contemporary Smartphone’s;(2) The increasing availability and ...The Internet of things has particularly novel implications in the area of public health. This is due to (1) The rapid and widespread adoption of powerful contemporary Smartphone’s;(2) The increasing availability and use of health and fitness sensors, wearable sensor patches, smart watches, wireless-enabled digital tattoos and ambient sensors;and (3) The nature of public health to implicitly involve connectivity with and the acquisition of data in relation to large numbers of individuals up to population scale. Of particular relevance in relation to the Internet of Things (IoT) and public health is the need for privacy and anonymity of users. It should be noted that IoT capabilities are not inconsistent with maintaining privacy, due to the focus of public health on aggregate data not individual data and broad public health interventions. In addition, public health information systems utilizing IoT capabilities can be constructed to specifically ensure privacy, security and anonymity, as has been developed and evaluated in this work. In this paper we describe the particular characteristics of the IoT that can play a role in enabling emerging public health capabilities;we describe a privacy-preserving IoT-based public health information system architecture;and provide a privacy evaluation.展开更多
Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector provisioning.Additionally,clinical data(particularly,medical image data)are ...Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector provisioning.Additionally,clinical data(particularly,medical image data)are a delicate,highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs.Herein,we propose an energy-efficient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server.The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed(decrypted)images.In this study,the decrypted image quality is preserved by the peak signal-to-noise ratio(PSNR)such that consumers can generate precise medical reports from IoHT devices at the application level.Moreover,a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud server.Experimental results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.展开更多
Background: Patients and public are increasingly relying on Internet for health information. Health care providers are using internet for dissemination of health information. However, health information available on i...Background: Patients and public are increasingly relying on Internet for health information. Health care providers are using internet for dissemination of health information. However, health information available on internet is not well regulated, and information quality varies greatly. Malaria is the leading cause of death and disease in many developing countries and has serious health burden around the world. The Internet could become a major resource for malaria education and information in Africa. This may potentially save millions of lives. The purpose of this study is to evaluate the quality of malaria health and treatment information available on the internet provided by the Nigerian context. Methods: Two key terms (malaria & treatment) were entered into three search engines: Google, Yahoo! and Bing. In order to retrieve articles as if the searches were conducted in Nigeria, the Local Area Network (LAN) settings were changed to a Nigerian proxy server, with a local Internet Protocol address. Three raters evaluated the quality of information using the DISCERN [9] instrument criteria. Kendall’s concordance coefficient (W) was calculated to determine the level of agreement among the three raters. Results: Thirty-eight websites evaluated, and the highest inter-rater average score was attributed to the Patient.co.uk website, followed by Wikipedia web site and Malaria Site. The “Home Remedies for You” website received the lowest score. Most evaluated websites were .com domains. The highest average score was given to .co.uk domains while .int had the lowest score. Conclusions: Improving the quality of malaria-related health information could lead to empowering communities, engaging and assisting them to strengthen their health and social information sharing and support.展开更多
Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the eff...Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.展开更多
Background: Today’s parents belong to the digital generation and regularly use the Internet as a source of information. Parents’ quests for health-related online information comprise an effort to manage symptoms of ...Background: Today’s parents belong to the digital generation and regularly use the Internet as a source of information. Parents’ quests for health-related online information comprise an effort to manage symptoms of illness or address questions about child development which may be an expression of self-management or self-care. Purpose: This study aims to describe health and child development related Internet search patterns used by parents of children ages zero to six, and further, how the obtained information was used in contacts with Child Health Care. Design and Methods: A two-step mixed- method approach is used in this study, comprising both a quantitative and a qualitative approach. First, a questionnaire was distributed to parents (n = 800) at 13 health centers in a medium sized county in Sweden. Second, one narrative interview with two parents total was conducted. Descriptive and non-parametric statistics were calculated, and qualitative manifest content analyses were performed. Results: A total of 687 completed the questionnaire, which corresponds to a response rate of 86%. The results show that 97% used the Internet for health-related and developmental child issues. The results show that parents often look at basic tips and the Internet is seen as a fast and accessible forum to obtain information. Parents often initiated their Internet searches using Google search for the specific subject, but the most common and most used website (used by 95% of parents), was the Swedish health site 1177.se. 98.4% of parents evaluated the general information searches they made on the Internet as reliable despite only 31% of the parents checking to see if the websites they used were scientifically based. Parents (81.7%) stated that they wanted their Child Health Nurses (CHN) to give them recommendations for valid websites. Conclusions: The results in this study show that, on the one hand, the Internet could strengthen parental knowledge (support self-care capacity), but, on the other hand, the found information could worry them and increase their anxiety—negatively affected self-care capacity. The parents suggested that the information should be double-checked to establish trust and develop self-care knowledge. Having a good resource to rely on, such as personal contact with a CHN, or using reliable websites seems to strengthen and reassure parents.展开更多
文摘Internet of Health Things(IoHT)is a subset of Internet of Things(IoT)technology that includes interconnected medical devices and sensors used in medical and healthcare information systems.However,IoHT is susceptible to cybersecurity threats due to its reliance on low-power biomedical devices and the use of open wireless channels for communication.In this article,we intend to address this shortcoming,and as a result,we propose a new scheme called,the certificateless anonymous authentication(CAA)scheme.The proposed scheme is based on hyperelliptic curve cryptography(HECC),an enhanced variant of elliptic curve cryptography(ECC)that employs a smaller key size of 80 bits as compared to 160 bits.The proposed scheme is secure against various attacks in both formal and informal security analyses.The formal study makes use of the Real-or-Random(ROR)model.A thorough comparative study of the proposed scheme is conducted for the security and efficiency of the proposed scheme with the relevant existing schemes.The results demonstrate that the proposed scheme not only ensures high security for health-related data but also increases efficiency.The proposed scheme’s computation cost is 2.88 ms,and the communication cost is 1440 bits,which shows its better efficiency compared to its counterpart schemes.
基金the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia through the project number(IFP2021-043).
文摘Falling is among the most harmful events older adults may encounter.With the continuous growth of the aging population in many societies,developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes essential.This paper presents a new healthcare Internet of Health Things(IoHT)architecture built around an ensemble machine learning-based fall detection system(FDS)for older people.Compared to deep neural networks,the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal hyperparameters.The number of cascaded random forest stages is automatically optimized.This study uses a public dataset of fall detection samples called SmartFall to validate the developed fall detection system.The SmartFall dataset is collected based on the acquired measurements of the three-axis accelerometer in a smartwatch.Each scenario in this dataset is classified and labeled as a fall or a non-fall.In comparison to the three machine learning models—K-nearest neighbors(KNN),decision tree(DT),and standard random forest(SRF),the proposed ensemble classifier outperformed the other models and achieved 98.4%accuracy.The developed healthcare IoHT framework can be realized for detecting fall accidents of older people by taking security and privacy concerns into account in future work.
基金Baoding Science and Technology Plan Project(Grant number:2041ZF311)。
文摘Objective:To observe the status quo of patients’psychological distress,and to explore the effect of Internet+health education model(IHEM)on patients who experienced psychological distress during their first hemodialysis treatment,with the goal of reducing their psychological distress and improving their quality of life.Methods:IHEM was conducted on 120 first-time hemodialysis patients for 3 months while a distress thermometer and a list of questionnaires were used to screen patients and provide corresponding psychological intervention.The incidence rate of psychological distress was analyzed statistically to explore the difference in psychological distress at various periods.Results:The incidence rate(score≥4)of psychological distress in first-time hemodialysis patients was 46.67%,and their distress was mainly rooted in physical,emotional,practical problems(economy,time,and energy),etc.Through IHEM,the psychological distress scores of the patients decreased to 3.29±1.02 at one month after their discharge,and the incidence rate was 32.14%;the psychological distress scores of the patients were 2.29±1.02 at 3 months after their discharge,and the incidence rate was 21.14%.The difference before and after the intervention was statistically significant(P<0.05).Conclusion:A psychological distress thermometer can timely detect the degree and causes of psychological distress among first-time hemodialysis patients,and the use of IHEM may significantly alleviate the psychological distress among hemodialysis patients.
文摘The Internet of things has particularly novel implications in the area of public health. This is due to (1) The rapid and widespread adoption of powerful contemporary Smartphone’s;(2) The increasing availability and use of health and fitness sensors, wearable sensor patches, smart watches, wireless-enabled digital tattoos and ambient sensors;and (3) The nature of public health to implicitly involve connectivity with and the acquisition of data in relation to large numbers of individuals up to population scale. Of particular relevance in relation to the Internet of Things (IoT) and public health is the need for privacy and anonymity of users. It should be noted that IoT capabilities are not inconsistent with maintaining privacy, due to the focus of public health on aggregate data not individual data and broad public health interventions. In addition, public health information systems utilizing IoT capabilities can be constructed to specifically ensure privacy, security and anonymity, as has been developed and evaluated in this work. In this paper we describe the particular characteristics of the IoT that can play a role in enabling emerging public health capabilities;we describe a privacy-preserving IoT-based public health information system architecture;and provide a privacy evaluation.
文摘Fog computing in the Internet of Health Things(IoHT)is promising owing to the increasing need for energy-and latency-optimized health sector provisioning.Additionally,clinical data(particularly,medical image data)are a delicate,highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs.Herein,we propose an energy-efficient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server.The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed(decrypted)images.In this study,the decrypted image quality is preserved by the peak signal-to-noise ratio(PSNR)such that consumers can generate precise medical reports from IoHT devices at the application level.Moreover,a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud server.Experimental results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.
文摘Background: Patients and public are increasingly relying on Internet for health information. Health care providers are using internet for dissemination of health information. However, health information available on internet is not well regulated, and information quality varies greatly. Malaria is the leading cause of death and disease in many developing countries and has serious health burden around the world. The Internet could become a major resource for malaria education and information in Africa. This may potentially save millions of lives. The purpose of this study is to evaluate the quality of malaria health and treatment information available on the internet provided by the Nigerian context. Methods: Two key terms (malaria & treatment) were entered into three search engines: Google, Yahoo! and Bing. In order to retrieve articles as if the searches were conducted in Nigeria, the Local Area Network (LAN) settings were changed to a Nigerian proxy server, with a local Internet Protocol address. Three raters evaluated the quality of information using the DISCERN [9] instrument criteria. Kendall’s concordance coefficient (W) was calculated to determine the level of agreement among the three raters. Results: Thirty-eight websites evaluated, and the highest inter-rater average score was attributed to the Patient.co.uk website, followed by Wikipedia web site and Malaria Site. The “Home Remedies for You” website received the lowest score. Most evaluated websites were .com domains. The highest average score was given to .co.uk domains while .int had the lowest score. Conclusions: Improving the quality of malaria-related health information could lead to empowering communities, engaging and assisting them to strengthen their health and social information sharing and support.
基金supported by National Natural Science Foundation of China(NSFC)under Grant Number T2350710232.
文摘Real-time health data monitoring is pivotal for bolstering road services’safety,intelligence,and efficiency within the Internet of Health Things(IoHT)framework.Yet,delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems.We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this.This strategy is devised to streamline the data retrieval path,subsequently diminishing network strain.Crafting an adept cache processing scheme poses its own set of challenges,especially given the transient nature of monitoring data and the imperative for swift data transmission,intertwined with resource allocation tactics.This paper unveils a novel mobile healthcare solution that harnesses the power of our collaborative caching approach,facilitating nuanced health monitoring via edge devices.The system capitalizes on cloud computing for intricate health data analytics,especially in pinpointing health anomalies.Given the dynamic locational shifts and possible connection disruptions,we have architected a hierarchical detection system,particularly during crises.This system caches data efficiently and incorporates a detection utility to assess data freshness and potential lag in response times.Furthermore,we introduce the Cache-Assisted Real-Time Detection(CARD)model,crafted to optimize utility.Addressing the inherent complexity of the NP-hard CARD model,we have championed a greedy algorithm as a solution.Simulations reveal that our collaborative caching technique markedly elevates the Cache Hit Ratio(CHR)and data freshness,outshining its contemporaneous benchmark algorithms.The empirical results underscore the strength and efficiency of our innovative IoHT-based health monitoring solution.To encapsulate,this paper tackles the nuances of real-time health data monitoring in the IoHT landscape,presenting a joint edge-cloud caching strategy paired with a hierarchical detection system.Our methodology yields enhanced cache efficiency and data freshness.The corroborative numerical data accentuates the feasibility and relevance of our model,casting a beacon for the future trajectory of real-time health data monitoring systems.
文摘Background: Today’s parents belong to the digital generation and regularly use the Internet as a source of information. Parents’ quests for health-related online information comprise an effort to manage symptoms of illness or address questions about child development which may be an expression of self-management or self-care. Purpose: This study aims to describe health and child development related Internet search patterns used by parents of children ages zero to six, and further, how the obtained information was used in contacts with Child Health Care. Design and Methods: A two-step mixed- method approach is used in this study, comprising both a quantitative and a qualitative approach. First, a questionnaire was distributed to parents (n = 800) at 13 health centers in a medium sized county in Sweden. Second, one narrative interview with two parents total was conducted. Descriptive and non-parametric statistics were calculated, and qualitative manifest content analyses were performed. Results: A total of 687 completed the questionnaire, which corresponds to a response rate of 86%. The results show that 97% used the Internet for health-related and developmental child issues. The results show that parents often look at basic tips and the Internet is seen as a fast and accessible forum to obtain information. Parents often initiated their Internet searches using Google search for the specific subject, but the most common and most used website (used by 95% of parents), was the Swedish health site 1177.se. 98.4% of parents evaluated the general information searches they made on the Internet as reliable despite only 31% of the parents checking to see if the websites they used were scientifically based. Parents (81.7%) stated that they wanted their Child Health Nurses (CHN) to give them recommendations for valid websites. Conclusions: The results in this study show that, on the one hand, the Internet could strengthen parental knowledge (support self-care capacity), but, on the other hand, the found information could worry them and increase their anxiety—negatively affected self-care capacity. The parents suggested that the information should be double-checked to establish trust and develop self-care knowledge. Having a good resource to rely on, such as personal contact with a CHN, or using reliable websites seems to strengthen and reassure parents.
