Personal Health Care Research Articles

Long-Term Efficacy of an AI-Based Health Coaching Mobile App in Slowing the Progression of Non-Dialysis Dependent CKD: A Retrospective Cohort Study.

Chronic kidney disease (CKD) is a significant public health concern, with an escalating global prevalence ranging from 11% to 13%. Therefore, practical strategies for slowing CKD progression and improving patient outcomes are imperative. There is limited evidence to substantiate the efficacy of mobile app-based nursing systems for decelerating CKD progression. This study aimed to evaluate the long-term efficacy of the KidneyOnline intelligent care system in slowing the progression of non-dialysis-dependent CKD. In this retrospective study, the KidneyOnline app was utilized for CKD patients in China who were registered between January 2017 and April 2023. Patients were divided into two groups: an intervention group using the app's nurse-led, patient-oriented management system and a conventional care group that didn't use the app. Patients' uploaded health data were processed via deep learning optical character recognition, and the AI system provided personalized healthcare plans and interventions. Conversely, the conventional care group received suggestions from nephrologists during regular visits without AI assistance. Monitoring extended for an average duration of 2.1 years post-recruitment, with the study's objective being to assess the app's effectiveness in preserving kidney function. The primary outcome was the eGFR slope over the follow-up period, and secondary outcomes included changes in albumin-to-creatinine ratio (ACR) and mean arterial pressure (MAP). A total of 12297 eligible patients who registered on the KidneyOnline app from January 2017 to April 2023 were enrolled for the analysis. Among them, 808 patients were successfully matched using 1:1 propensity score matching, resulting in 404(50%) patients in the KidneyOnline care system group and another 404(50%) patients in the conventional care group. The eGFR slope in the KidneyOnline care group was significantly lower than that in the conventional care group (-1.3, 95% CI: -2.4, -0.1 mL/min/1.73 m2 per year vs. -2.8, 95% CI: -3.8, -1.9 mL/min/1.73 m2 per year，P=.009). Subgroup analysis revealed that the effect of the KidneyOnline care group was more significant in males, patients over 45 years old, and patients with worse baseline kidney function, higher blood pressure, and heavier proteinuria. After 3 and 6 months, the MAP in the KidneyOnline care group decreased to 85.6 (SD 9.2) and 83.6 (SD 10.5) mmHg, respectively, compared to 94.9 (SD 10.6) and 95.2 (SD 11.6) mmHg in the conventional care group (P<.001). The ACR in the KidneyOnline care group showed a more significant reduction after 3 and 6 months (736 mg/g vs. 980 mg/g and 572 mg/g vs. 840 mg/g, P=.074, .027)); however, there was no significant difference in ACR between the two groups at the end of the follow-up period (618 mg/g vs. 639 mg/g, P=.904). The utilization of KidneyOnline, an AI-based, nurse-led, patient-centered care system, may be beneficial in slowing the progression of non-dialysis-dependent CKD.

Highly Sensitive Flexible Sensors for Human Activity Monitoring and Personal Healthcare.

Flexible sensors are capable of converting multiple human physiological signals into electrical signals for various applications in clinical diagnostics, athletics, and human-machine interaction. High-performance flexible strain sensors are particularly desirable for sensitive, reliable, and long-term monitoring, but current applications are still constrained due to high response threshold, low recoverability properties, and complex preparation methods. In this study, we present a stable and flexible strain sensor by a cost-effective self-assemble approach that demonstrates remarkable sensitivity (2169), ultrafast response and recovery time (112 ms), and wide dynamic response range (0-50%), as confirmed in human pulse and human-computer interaction. These excellent performances can be attributed to the design of a Polydimethylsiloxane (PDMS) substrate integrated with multiwalled carbon nanotubes (MWCNT) and graphene nanosheets (GNFs), which results in high electrical conductivity. The MWCNT serves as a bridge, connecting the GNFs to create an efficient conductive path even under a strain of 50%. We also demonstrate the strain sensor's capability in weak physiological signal pulse measurement and excellent resistance to mechanical fatigue. Moreover, the sensor shows diverse sensitivities in various tensile states with different signal patterns, making it highly suitable for full-range human monitoring and flexible wearable systems.

Data sharing decisions: Perceptions and intentions in healthcare

AbstractThis article aimed to capture and understand individual's intentions to share data, focusing on data individuals perceive as most sensitive: healthcare data. The study reviews literature related to the decision‐making process with regard to sharing personal data. The context is the UK National Health Service, and measures from literature are used to analyze individual's intention to share healthcare data. A scale is developed and applied to evaluate the decision to share healthcare data. Measurement constructs include intention to disclose, perceived protection, benefits, risk, subjective norms, and perception of use. Analysis draws on data from 129 survey respondents. Though numerous measurements are reported in literature and used in this study, two predictors dominate intention to disclose healthcare data: perceived information risk (PIR) and perceived societal benefit (PSB), and both are significant. PIR contributes negatively, whereas PSB contributes positively to predict intention. For personal healthcare, the privacy paradox applies as though risk may outweigh benefit people rarely opt out of data sharing. Individuals consciously or unconsciously consider their perception of the risk and broader benefits of data sharing. Both risk and benefit are both significant and important; perceived risk carries more weight than perceived benefits. Organizations need to develop campaigns to very clearly explain risks and benefits of personal data sharing to ensure that individuals can make truly informed decisions.

Association of Personal Wealth Indicators and Health Care Costs in Persons With Alzheimer's Disease

ObjectivesThere is paucity of studies on the relationship between personal wealth and health care costs among persons with dementia, and earlier studies on other indicators of socioeconomic position have assessed costs after dementia diagnosis only. We investigated how different indicators of personal wealth (disposable income, supplementary income, assets subject to taxation, taxes and tax-like payments, and liabilities) are associated with health care costs in persons with Alzheimer's disease (AD) before and after AD diagnosis. DesignRegister-based nationwide cohort study of persons with AD. Setting and ParticipantsCohort of 70,531 people who received a clinically verified AD diagnosis in Finland between 2005 and 2011 and were community-dwelling at time of diagnosis. MethodsData on income indicators were obtained from Statistics Finland. Data on medication costs and hospital care costs for the 12-month period from 5 years before to 2 years after AD diagnosis were obtained from national registers. Associations of wealth indicators with costs were investigated with multivariate mixed-effect negative binomial regression. ResultsAfter adjustment for age, region, sex, marital status, comorbidities, expensive medications, use of psychotropic and antidementia medication, and highest occupational class before AD, people with higher levels of personal wealth indicators were more likely to have higher total health care costs along the whole follow-up period. The incidence rate ratios (IRRs), 95% CI for highest quintile vs lowest quintile were 1.17, 1.15−1.19 for disposable income, 1.10, 1.08−1.12 for taxable income, 1.18, 1.16−1.19 for supplementary income, 1.07, 1.06−1.09 for taxes, and 1.05, 1.04−1.07 for taxable wealth. Conclusions and ImplicationsOur observation on the association between income/wealth indicators and health care costs in a country with a strong public health care system call for more effective measures in targeting health inequalities in the aging population. Although the different indicators were not completely interchangeable, associations of different indicators were toward the same direction.

Being a woman or being a youth: what matters for young adults with chronic diseases?

Abstract Background as the prevalence of chronic diseases increases with age, most interventions focus on ‘adults’ and neglect the growing proportion of chronically ill young people aged 15-24. Although they are no longer children, they are still in a period of transition towards autonomy and independence, particularly in industrialised countries. Moreover, health care for chronic patients is criticised for neglecting gender-specific needs. This exploratory collaborative study identified needs and preferences of youths living with a chronic disease with a gender lens. Methods we conducted 24 semi-directive interviews: 12 university students living with rare or chronic diseases; 12 health care professionals (doctors, nurses and allied health professionals). We conducted a group interview with an interdisciplinary staff in hospital and a group interview in an integrated primary care centre in 2022 in Brussels, Belgium. Alongside thematic analysis of the content of the interviews, we used the group analysis method with youths and professionals to co-construct recommendations: data were analysed and discussed in several collaborative meetings. Results youths insisted that professionals should listen more to youths and be more flexible. Youths stressed the need for psychological support currently absent, support regarding educational trajectory and warm environment of care similar to paediatric settings. Professionals expressed their concerns about being more gender-friendly and their lack of training regarding gender issues and other non-medical aspects of chronic diseases. Both youths and professionals consider gender-specific needs in a larger frame of patient-centred care focusing on the integration of patient preferences in a co-constructed dialogue. Conclusions to be youth-friendly, health services should better embrace the personalised health care planning, allowing for a better inclusion of what really matters for youths, be their age or their gender. Key messages • Personnalised health care planning supports gender-friendly health services. • Personnalised health care planning supports youth-friendly health services.

Implementation of precision medicine in (routine) cancer care in Belgium in a fair and equitable way

Abstract Background Personalized medicine has been found to be highly promising in the prevention or early detection of cancers. Despite the advantages, the scope and potential of personalized health care are under-appreciated and underrealized in health systems. Taking into account the advantages that personalized medicine can bring to cancer prevention and treatment, and acknowledging at the same time the trends happening outside of the field of oncology, Sciensano Cancer Centre conducted research on the use of personalized medicine in the Belgian healthcare system. Methods By applying foresight methodology, we first conducted desk research and sent a survey to experts; this was then followed by two stakeholder meetings where we discussed the importance and uncertainties of the factors that have an influence on the implementation of precision medicine in (routine) cancer care in Belgium in a fair and equitable way and developed future scenarios accordingly. Results The main influential factors are concerned with economic issues, such as the allocated budget in the healthcare system. Similarly, technological factors around precision medicine should not be neglected: especially issues concerning digitalization will be decisive to determine the future of precision medicine in Belgium. Conclusions With the increasing prevalence and incidence of cancer in Belgium, several factors should be considered to implement precision medicine for cancer prevention and treatment in a fair and equitable way. Strategic foresight on precision medicine can support decision-makers in these tasks and help them develop future-oriented policies.

Cost-effectiveness analysis of Next generation sequencing tests in critically ill pediatric patients

Abstract Rare genetic diseases in the pediatric population constitute an urgent global public health issue; overall, more than 300 million people are affected worldwide. Next Generation Sequencing techniques, as Whole genome sequencing (WGS) and Whole exome sequencing (WES), have proven to be significantly supportive in diagnosing these complex conditions. The aim is to evaluate the cost-effectiveness of WGS versus WES in pediatric patients with suspected genetic disorders. A Bayesian Markov model was calibrated among this target population, comparing WGS to WES. Model parameters were retrieved from the scientific literature. Costs and benefits were discounted at a rate of 3%. A lifetime time horizon and the National Health Service perspective was chosen. The Eurozone threshold, ranging from €30,000 to €50,000, was adopted. Markov Chain Monte Carlo was used as the simulation method for Bayesian inference. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI), illustrated through Cost-Effectiveness Acceptability Curve (CEAC) and Expected Value of Perfect Information (EVPI). Results were reported as Incremental Cost-Effectiveness Ratio (ICER), expressed as euros per additional diagnosis. The base case findings highlighted that WGS was cost-effective with an ICER of €31,973. The CEAC showed that for all thresholds over the ICER, WGS had the highest probability of being cost-effective. The EVPI per patient was estimated to be €6,535 on a threshold of €50,000/diagnosis. In addition to being cost-effective, WGS could allow early genetic diagnosis shortening the diagnostic odyssey. The use of WGS in the diagnostic workup has the potential to revolutionise personalised medicine and to play a significant role in achieving SDG 3 by providing personalised healthcare, identifying genetic risk factors for diseases, and informing public health policies for a target population that represents the human capital of the future. Key messages • This analysis informs that WGS is cost-effective and possibly cost-saving in the long term. • WGS could be implemented in the diagnostic workup of children with suspected rare disorders.

The Role of The Internet of things in Healthcare Transformation

The internet of things (IoT) must now be enhanced in the eraof the industrial revolution 4.0 to simplify healthcare andincrease its effectiveness in monitoring patients' healthconditions remotely.The Internet of Things (IoT) is a globalnetwork of interconnected computing devices that includespeople, machines, and other living things. Each of thesedevices has been given a unique identifier and has the abilityto send and receive data over the network without the need fordirect human or machine-to-human communication.Connectivity, standards, smart analytics, smart actions,networks, sensors, smart analytics, devices, cloud, and userinterfaces are some of the elements of the Internet of Things.IoT transformation in personal healthcare can be classifiedinto in-clinic care and remote monitoring. IoT security systemsand patient data protection must be carefully considered toprevent data leakage or improper processing of health dataobtained through the use of IoT. To make the most of IoT, thegrowth of IoT in the healthcare industry must be matched bylaws and regulations governing personal data security.

Detection and Correction of Yoga Poses

Yoga is a highly beneficial physical activity with promising applications in personal healthcare. Multiple studies have demonstrated that yoga can serve as a physical treatment for various health issues, such as cancer, musculoskeletal disorders, depression, Parkinson's disease, and respiratory and heart diseases, among others. Proper body alignment is critical in yoga, requiring effort on the muscles, ligaments, and joints to achieve the optimal posture. Postural-based yoga can improve flexibility, energy, and brain activity, and reduce stress, blood pressure, and back pain. During yogic asanas, proper body alignment is crucial to avoid strain on the joints, ligaments, and backbone, particularly during forward or backward bending asanas such as uttanasana, kurmasana, ustrasana, and dhanurasana. To ensure correct poses while performing different asanas, it is essential to monitor body posture alignment. Advancements in computer vision algorithms and sensors have made it possible to predict yoga posture and automatically analyse movement. Therefore, practitioners can now leverage technology to enhance their yoga practice and achieve better results. This paper proposes a method to analyse the yoga postures performed by the user and correct them in real time.

Health care functions of ozone sterilizer

People’s Daily life and physical health are often plagued by viruses and bacteria. The novel coronavirus epidemic several years ago has seriously affected the global economy and social life. In addition to vaccination, ecologically safe and long-term and effective disinfection methods are very necessary. Ozone is an efficient and broad-spectrum bactericidal disinfectant, and the trace level of ozone in the atmosphere can make many viruses and bacteria lose their biochemical activity and infectivity. Nature produces trace amounts of ozone in the air through lightning to achieve the purpose of purifying the ecological environment. The product of ozone decomposition is oxygen, without secondary pollution. Ozone sterilizer has been widely used in epidemic prevention and control in intensive breeding farms and has achieved remarkable effects. If the concentration and action time can be accurately controlled, then ozone can effectively eliminate pathogens without harming normal cells in the human body. Therefore, the use of mini household ozone disinfectors for personal epidemic prevention and health care is a topic worth serious research. Shanghai Finerule Company has done a lot of tentative work in this respect and has achieved some good results.

Uncovering the Work-Family Interface: The Impact of Facilitators and Stressors on the Health of Farm Women.

Work-family interface (WFI) theory has identified many stressors that influence work-family dynamics from the standpoint of employees. However, work-family facilitators, as well as the effects of gender differences and the impact of sociocultural environments that differ from a formal employment situation, have received much less attention. Our research aimed to fill these theoretical gaps by analyzing the facilitators and stressors involved in work-family dynamics and determining their consequences for farm women's physical, psychological, and social health. We used a qualitative method with a grounded theory design to collect data via semi-structured interviews with 46 farm women from the region of Araucanía in Chile. Our results explain how facilitators, stressors, and outcomes take place in a process of work-family balance that, paradoxically, implies exhausting journeys, a gender-based overload, a risk of diffuse body pain and distress, and a lack of time for personal healthcare and productive autonomy. Addressing these issues requires a comprehensive approach involving improved healthcare infrastructure and services focused on changing the pressures that the farming WFI exerts on rural women.

A Hybrid Genetic Algorithm-Based Random Forest Model for Intrusion Detection Approach in Internet of Medical Things

The Internet of Medical Things (IoMT) is a bio-network of associated medical devices, which is slowly improving the healthcare industry by focusing its abilities on enhancing personal healthcare benefits with medical data. Moreover, the IoMT tries to deliver sufficient and more suitable medical services at a low cost. With the rapid growth of technology, medical instruments that are widely used anywhere are likely to increase security issues and create safe data transmission issues through resource limitations and available connectivity. Moreover, the patients probably face the risk of different forms of physical harm because of IoMT device attacks. In this paper, we present a secure environment for IoMT devices against cyber-attacks for patient medical data using a new IoMT framework with a hybrid genetic algorithm-based random forest (GA-RF) model. The proposed algorithm achieved better results in terms of accuracy (99.999%), precision, and recall (100%, respectively) to detect cyber-attacks based on two NSL-KDD and UNSW_2018_IoT_Botnet data sets than the other machine learning algorithms.

Futuristic frontiers in science and technology: Advancements, requirements, and challenges of multi-approach research

&lt;p&gt;The rapid advancement of science and technology necessitates a multidisciplinary research approach to address complex challenges and unlock transformative innovation. This short communication paper discusses the future requirements and challenges associated with the integration of the latest technologies, including Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Medical Imaging, Electronic Health Records (EHR), Precision Medicine, Personalized Healthcare, Clinical Decision Support Systems, AI-Based Screening Systems, Federated Learning, and Point Cloud Processing. By understanding these requirements and challenges, researchers can navigate the multidisciplinary landscape and leverage technology’s potential for scientific progress.&lt;/p&gt;

A multifunctional sensor for real-time monitoring and pro-healing of frostbite wounds

Flexible epidermal sensors based on conductive hydrogels hold great promise for various applications, such as wearable electronics and personal healthcare monitoring. However, the integration of conductive hydrogel epidermal sensors into multiple applications remains challenging. In this study, a multifunctional PAAm/PEG/hydrolyzed keratin (Hereinafter referred to as HK)/MXene conductive hydrogel (PPHM hydrogel) was designed as a high-performance therapeutic all-in-one epidermal sensor. This sensor not only accelerates wound healing but also provides wearable human-computer interaction. The developed sensor possesses highly sensitive sensing properties (Gauge Factor = 4.82 at high strain), strong mechanical tensile properties (capable of achieving a maximum elongation at break of 600 %), rapid self-healing capability, stable self-adhesive capability, biocompatibility, freeze resistance at −20 °C, and adjustable photo-thermal conversion capability. This therapeutic all-in-one sensor can sensitively monitor human movements, enabling the detection of small electrophysiological signals for diagnosing relevant activities and diseases. Furthermore, using a rat frostbite model, we demonstrated that the composite hydrogel sensor can serve as an effective wound dressing to accelerate the healing process. This study serves as a valuable reference for the development of multifunctional flexible epidermal sensors for personal smart health monitoring. Statement of significanceAccelerated wound healing reduces the risk of wound infection, and conductive hydrogel-based sensors can monitor physiological signals. The multifunctional application of conductive hydrogel sensors combined with wound diagnostic and therapeutic capabilities can meet personalized medical requirements for wound healing and sensor monitoring. The aim of this study is to develop a multifunctional hydrogel patch. The multifunctional hydrogel can be assembled into a flexible wearable high-performance diagnostic and therapeutic integrated sensor that can effectively accelerate the healing of frostbite wounds and satisfy the real-time monitoring of multi-application scenarios. We expect that this study will inform efforts to integrate wound therapy and sensor monitoring.

Patient Interest in Exploring Nonsurgical Treatment Approaches for Early-Stage Breast Cancer: A Qualitative Study

IntroductionAdvances in radiotherapy have enabled the ability to deliver ablative treatments, but there has been limited application of these treatments to early stage breast cancers with a goal of omitting surgery. The purpose of this study was to explore patient interest in pursuing non-surgical treatment approaches for their early stage breast cancer. Material and MethodsWe conducted a qualitative study involving interviews with 21 patients with early stage breast cancer who were eligible for participation in a phase II clinical trial offering omission of definitive surgery. Interviews were transcribed and an inductive, thematic analysis was performed by three independent reviewers to generate themes and subthemes. ResultsData analysis revealed the following factors that impacted patient willingness and desire to explore non-surgical treatment options: 1) Perceptions and feelings about their cancer; 2) Current quality of life and the level of support available in their daily life; 3) External conversations focusing on family members’ and friends’ experiences with cancer and/or cancer treatments; 4) Personal healthcare experiences, including their current breast cancer diagnosis; 5) Perceptions and feelings about their physicians; 6) Conversations with their physicians about their treatment options; and 7) Self-identified desire to direct care decisions. Specifically, patients verbalized fearing surgery and surgical recovery, wanting to preserve their breast(s), the prior negative surgical experiences of friends, family and themselves, a desire to receive treatment per the latest research, wanting to match the level of treatment with the severity of their cancer, and other comorbidities as reasons for wanting to explore omitting surgery. DiscussionOur findings demonstrate an unmet need directed by patient interest to explore non-surgical options for early stage, biologically favorable breast cancer. These results may shape conversations around shared decision making, clinical trial design, and result in more personalized treatment options for women with early stage breast cancer.

Towards a personalized health care using a divisive hierarchical clustering approach for comorbidity and the prediction of conditioned group risks.

The objective was to assess risk of hospitalization and mortality of comorbidities using divisive hierarchical risk clustering to advice clinical interventions. Subjects and Methods: Data from the EHR of a general population, 3799885 adults, followed by 5 years. Model were performed using Spark and Scikit-learn and accuracy for the models was analyzed. Results: The number of models generated depends in part on the number of chronic diseases included (ex testing a sample of six diseases, a total number of 397 models for all-cause mortality and 431 models for hospitalization). The estimated models offered an ordered selection for the relevant clinical variables and their estimated risk as a group and for the individual patient in the group. Accuracy was assessed according to age, sex and the cardinality of the comorbid groups. A mobile version and dashboard were developed. Conclusion: The software developed stratified hospital admission and mortality risk in clusters of chronic diseases, and for a given patient, it could advise intensifying treatment or reallocating the patient risk.

Is the Clinical Practicum in Addiction Treatment Facilities an Effective Educational Intervention to Improve Nursing Students' Attitudes Toward Alcohol Use Disorders?

The paucity of education and training on alcohol use disorders (AUDs) in nursing curricula is the main predictor of negative attitudes and results in limited knowledge access and delivery of health care for persons experiencing these problems. Although experts advocate increasing the time devoted to alcohol-related content in a crowded curriculum, didactic strategies for teaching about addiction in prequalifying nursing education have been discussed. This study aimed to verify the effectiveness of an educational experience that integrated clinical practicum experience in addiction treatment facilities for nursing students' attitudes. A quasi-experimental one-group study with pre-and-post 3-month follow-ups was carried out with 108 nursing students who answered the Attitudes Scale toward Alcohol, Alcohol Use Disorder, and Patients with Alcohol Use Disorders. The effect of the clinical practicum was apparent, with statistically significant changes to more positive global attitude scores in all measures. Previous educational intervention for AUDs during nursing education was a predictor of positive attitudes (OR = 7.21, p < .04). Students' self-perceived skills and professional preparation to deliver and direct care for patients with AUDs improved after the intervention, suggesting that clinical practice influenced students' skills for AUD identification across nursing practice. Previous contact with this population with lack of training in substance use disorder seems to favor negative attitude development. Clinical practicum experience in addiction treatment facilities improved nursing students' attitudes toward AUDs and patients with AUDs, and its effects were sustained 3 months later.

Personal Healthcare Management through Social Media: A Study of Graduate Students in Selected Ethiopian Universities

Personal Healthcare Management through Social Media: A Study of Graduate Students in Selected Ethiopian Universities

Reevaluating Health Metrics: A Multi-Dimensional Approach Beyond BMI

Body Mass Index (BMI) has long served as a conventional metric to assess overall health, but its limitations have spurred a demand for more comprehensive health evaluation tools. This article investigates the shortcomings of BMI, such as its disregard for body composition, age, gender disparities, and potential ethnic biases. By focusing on alternative indicators of health, such as waist-to-hip ratio, body composition analysis, and cardiorespiratory fitness, we highlight the need for a more holistic health assessment. Emphasizing personalized healthcare, this article advocates for integrating various health metrics to gain a deeper understanding of an individual's well-being, leading to more accurate diagnoses and tailored interventions. Ultimately, adopting a multi-dimensional approach beyond BMI offers a promising avenue for enhancing healthcare practices and improving patient outcomes.

Blockchain-Based Personalized Federated Learning for Internet of Medical Things

The rapid growth of artificial intelligence (AI), blockchain technology, and edge computing services have enabled the Internet of Medical Things (IoMT) to provide various healthcare services to patients, including neural network-based disease diagnosis, heart rate monitoring, and fall detection. Generally, end devices should transmit the collected patient data to a centralized server for further model training, but at the same time, the patient's privacy may be at risk. In addition, due to the diversity of patient conditions, a one-size-fits-all model cannot meet personalized healthcare needs. To address the above challenges, we propose a blockchain-based personalized federated learning (FL) system that enables clients to participate in personalized model training without directly uploading private data. We further realize the decentralized FL by combining blockchain technology, which improves the security level of the system. Finally, we verify the reliable performance of our system on different datasets through simulation experiments.