Personal Health Care Research Articles

Health services consumption and barriers in the health care of persons of Roma origin in Bulgaria

Abstract Introduction Persons of Roma origin often face serious inequities concerning their state of health and their access to good quality health services. The aim of the study is to analyze the health services consumption and barriers in the health care of persons of Roma origin in Bulgaria. Methods The cross-sectional study was conducted and a semi-structured face to face interview were applied in 2022. Adult citizens of Roma origin were covered as follows: residents of Knezha - a total of 59 people and households from the towns of Knezha and Kotel - 18 families (50 persons). The cities are representative of settlements of medium size with separate neighborhoods of Roma origin. Data processing was performed by SPSS v.24. Results Over two thirds of the covered persons of Roma origin do not have health insurance. In each household an average of 1.8 uninsured people was found, but in some of the families almost all of the elderly members are not insured. Due to lack of health insurance in 14% of the households were reported a refusal to provide health care by general practitioners (GPs) and specialists in out-hospital care. 82.1% of Roma women have never had a mammography and 71.4% a smear test. In 83.3% of the households required direct payment for the provision of health services, which corresponds to the high share of informal payments in health care in Bulgaria (34 % in 2023), but among the Roma population this share is significantly higher. The households have to pay for specialized out-hospital care (66.6%), GPs (22.2%), and for emergency assistance (5,6%). 44.4% of the families have used the services of emergency care in the last one year. While in one third of the families an adult member was hospitalized in 27.8% of them there is a need for hospital treatment, which is unrealized. Conclusions The Roma population in Bulgaria is characterized by an unfavorable health profile and the health services provided to the persons of Roma origin are inadequate to their needs. Key messages • Persons of Roma origin in Bulgaria often face serious inequities concerning their state of health and their access to good quality health services. • Improving the socioeconomic status of people of Roma origin will increase their opportunities for health insurance and going to improve their access to health services.

Economic evaluation of Polygenic Risk Scores in healthcare interventions: a systematic review

Abstract Background Polygenic Risk Scores (PRS) quantify genetic susceptibility to diseases, promising personalized healthcare. This review explores current evidence regarding the economic evaluation of strategies based on PRS or other polygenic risk stratification approaches, scrutinizing their methodologies. Methods The study protocol was registered in PROSPERO (CRD42023442780). A systematic search in PubMed, Scopus, and Web of Science identified full economic evaluations of intervention based on polygenic risk stratification strategies. The quality of the included articles was assessed using the Drummond checklist. This study was supported by the EC and MUR under PNRR - M4C2-I1.3 Project PE_00000019 ‘HEAL ITALIA”. Results Nineteen articles were included in the analysis, with oncological conditions being the most frequently investigated (13), followed by cardiovascular conditions (3). In nearly 80% of the studies, PRS was employed for screening interventions, with the general population being the primary target in 14 out of the 19 studies. All the economic analysis models investigated cost-utility in terms of QALYs, with Markov models and microsimulations being the most common structures. The majority of these models were based on simulated cohorts derived mostly from North American or European data, with 9 adopting a healthcare system perspective and 6 a societal perspective. Although delivery strategies for PRS testing were rarely addressed, PRS costs were included in nearly all studies. Indirect costs were examined in fewer than half of the studies. In 12 out of 19 studies, the conclusions claimed the cost utility of PRS involving strategies. Conclusions Despite the technique’s potential, evaluations of various strategies based on PRS approaches yield heterogeneous conclusions regarding cost-utility. Our study highlights the factors contributing to this heterogeneity and underscores the need for further exploration, ideally prioritizing real-world data. Key messages • PRS strategies evaluations vary in cost-utility conclusions, highlighting the need for further investigation. • Real-world data and practical implications should be prioritised in PRS research.

Barriers and facilitators to healthcare services of people with mental ill-health in Europe

Abstract Background People with mental ill-health (PMIH) have higher cancer mortality rates than the general population. Barriers to healthcare service access may be a contributing factor. The EU-funded CO-CAPTAIN project aims to reduce health inequalities by improving overall health and reducing cancer burden by adapting and implementing the Patient Navigation (PN) Model targeted at PMIH. This qualitative study explored healthcare system experiences of PMIH in Austria, Greece, Poland, and Spain. Methods Eighty-one participants (22-76 years old), including 34 PMIH, 10 caregivers, 14 care team members, 12 mental health organization representatives, and 11 service manager representatives, were recruited. Semi-structured interviews focused on awareness of cancer risk factors, healthcare system experiences, and perspectives on PN as an intervention. Interviews were transcribed verbatim and analyzed using thematic analysis. Results Three major themes emerged: (1) somatic health relevance and preventive services utilization and (2) barriers / (3) facilitators to preventive services access. Knowledge of cancer prevention services varied greatly. Participants were aware of associations between risky health behaviors and health. Burden of mental health problems and discrimination, insufficient access to information, and lack of service flexibility were noted as barriers. Considerations of individual circumstances, social support, and empowerment were named as facilitators. Conclusions Tailored interventions involving healthcare professionals and PMIH in development of supportive environments and health literacy have the potential of overcoming identified barriers to the use of healthcare services. Key messages • People experiencing mental ill-health are faced with significant structural barriers when accessing somatic health services. • Understanding people’s needs in terms of access and utilization of health care allows us to define guidelines for future personalized healthcare solutions.

Systematic Review of Social Robots for Health and Wellbeing: A Personal Healthcare Journey Lens

Systematic Review of Social Robots for Health and Wellbeing: A Personal Healthcare Journey Lens

Smart Green Cotton Textiles with Hierarchically Responsive Conductive Network for Personal Healthcare and Thermal Management.

Whereas cotton as an abundant natural cellulose has been widely used for sustainable and skin-friendly textiles and clothes, developing cotton fabrics with smart functions that could respond to various stimuli is still eagerly desired while remaining a great challenge. Herein, smart multiresponsive cotton fabric with hierarchically copper nanowire interwoven MXene conductive networks that are seamlessly assembled along a 3D woven fabric template for efficient personal healthcare and thermal comfort regulation is successfully developed. The robust hierarchically interwoven conductive network was "glued" and protected by organic conductive polymer poly(3,4-ethylenedioxythiophene) along a 3D interconnected fabric template to enhance interfacial adherent and environmental stability. Benefiting from the robust multiresponsive hierarchically interwoven conductive network, smart cotton fabric exhibits real-time response to various external stimuli (light/electrical/heat/temperature/stress), and the details of human activities can be accurately recognized and monitored. Furthermore, the porous structure of 3D smart fabric induced strong capillary force and confinement to phase change materials PEG, which exhibits a wide range of phase transition temperatures for efficient thermal comfort regulation. After further encapsulation with transparent fluorosilicone resin, the smart cotton fabric exhibits excellent self-cleaning performance with water/oil repellent. The smart multiresponsive cotton fabrics hold great promise in next-generation wearable systems for efficient personal healthcare and thermal management.

Breathable and Stretchable Epidermal Electronics for Health Management: Recent Advances and Challenges.

Advanced epidermal electronic devices, capable of real-time monitoring of physical, physiological, and biochemical signals and administering appropriate therapeutics, are revolutionizing personalized healthcare technology. However, conventional portable electronic devices are predominantly constructed from impermeable and rigid materials, which thus leads to the mechanical and biochemical disparities between the devices and human tissues, resulting in skin irritation, tissue damage, compromised signal-to-noise ratio (SNR), and limited operational lifespans. To address these limitations, a new generation of wearable on-skin electronics built on stretchable and porous substrates has emerged. These substrates offer significant advantages including breathability, conformability, biocompatibility, and mechanical robustness, thus providing solutions for the aforementioned challenges. However, given their diverse nature and varying application scenarios, the careful selection and engineering of suitable substrates is paramount when developing high-performance on-skin electronics tailored to specific applications. This comprehensive review begins with an overview of various stretchable porous substrates, specifically focusing on their fundamental design principles, fabrication processes, and practical applications. Subsequently, a concise comparison of various methods is offered to fabricate epidermal electronics by applying these porous substrates. Following these, the latest advancements and applications of these electronics are highlighted. Finally, the current challenges are summarized and potential future directions in this dynamic field are explored.

Genomic instability and genetic heterogeneity in aging: insights from clonal hematopoiesis (CHIP), monoclonal gammopathy (MGUS), and monoclonal B-cell lymphocytosis (MBL).

Aging is a multifaceted process characterized by a gradual decline in physiological function and increased susceptibility to a range of chronic diseases. Among the molecular and cellular mechanisms driving aging, genomic instability is a fundamental hallmark, contributing to increased mutation load and genetic heterogeneity within cellular populations. This review explores the role of genomic instability and genetic heterogeneity in aging in the hematopoietic system, with a particular focus on clonal hematopoiesis of indeterminate potential (CHIP), monoclonal gammopathy of undetermined significance (MGUS), and monoclonal B-cell lymphocytosis (MBL) as biomarkers. CHIP involves the clonal expansion of hematopoietic stem cells with somatic mutations. In contrast, MGUS is characterized by the presence of clonal plasma cells producing monoclonal immunoglobulins, while MBL is characterized by clonal proliferation of B cells. These conditions are prevalent in the aging population and serve as measurable indicators of underlying genomic instability. Studying these entities offers valuable insights into the mechanisms by which somatic mutations accumulate and drive clonal evolution in the hematopoietic system, providing a deeper understanding of how aging impacts cellular and tissue homeostasis. In summary, the hematopoietic system serves as a powerful model for investigating the interplay between genomic instability and aging. Incorporating age-related hematological conditions into aging research, alongside other biomarkers such as epigenetic clocks, can enhance the precision and predictive power of biological age assessments. These biomarkers provide a comprehensive view of the aging process, facilitating the early detection of age-related diseases and hopefully enabling personalized healthcare strategies.

Primary Care Guidance for Providers of Care for Persons With Human Immunodeficiency Virus: 2024 Update by the HIV Medicine Association of the Infectious Diseases Society of America.

Advances in antiretroviral therapy (ART) have made it possible for persons with human immunodeficiency virus (HIV) to live a lifespan approaching that of people without HIV, without progressing to AIDS or transmitting HIV to sexual partners or infants. There is, therefore, increasing emphasis on maintaining health throughout the lifespan. To receive optimal medical care and achieve desired outcomes, persons with HIV must be consistently engaged in care and able to access uninterrupted treatment, including ART. Comprehensive evidence-based HIV primary care guidance is, therefore, more important than ever. Creating a patient-centered, stigma-free care environment is essential for care engagement. Barriers to care must be decreased at the societal, health system, clinic, and individual levels. As the population ages and noncommunicable diseases arise, providing comprehensive health care for persons with HIV becomes increasingly complex, including management of multiple comorbidities and the associated challenges of polypharmacy, while also attending to HIV-specific health concerns. Clinicians must address issues specific to preventive health, including cancer screening, providing recommended vaccinations, as well as promoting sexual health, including sexually transmitted infection diagnosis, treatment, and prevention. Clinicians also must address issues for specific populations, including persons of childbearing potential, including during preconception and pregnancy; children; adolescents; and transgender and gender-diverse individuals. This guidance from an expert panel of the HIV Medicine Association of the Infectious Diseases Society of America updates the previous 2020 HIV Primary Care Guidance.

Artificial Intelligence and Digital Biomarkers: A Revolution in Cardiovascular Diagnostics

THIS YEAR, the European Society of Cardiology (ESC) Congress 2024, which took place in London, UK, between 30th August–2nd September, hosted an insightful symposium entitled ‘Artificial intelligence unleashed on digital biomarkers: a new era in personalised cardiovascular healthcare’. The session explored the applications of AI in cardiac diagnostics, highlighting its potential to positively impact patient care. The speakers covered key topics, including how vascular retinal imaging could predict cardiovascular risk and whether speech analysis could aid in the detection of acute decompensated heart failure.

Long-lifespan, biodegradable, self-disinfecting, and gas-sensing electronic mask with a Janus-structured all-natural fiber network for personal healthcare

Conventional disposable surgical masks have become an integral part of our daily lives, however, present a limited filtration efficiency, brief operative lifespan, and inability to degrade naturally, bringing a heavy burden to the environment. Moreover, these masks cannot efficaciously eliminate bacteria, potentially causing secondary and cross infections among users, thereby failing to curb the spread of infectious diseases. Herein, a fire-new, long-lifespan, biodegradable, self-disinfecting, and gas-sensing electronic-mask is nano-engineered with a Janus-structured all-natural fiber network (SA-CPN) constructed from animal-collagen and plant-fibers. SA-CPN demonstrates exceptional filtration performance (99.9%) for PM2.5 and maintains outstanding filtration efficiency after 10 test-cycles or 32 h in high-humidity conditions. SA-CPN exhibits robust antibacterial origins for extended periods, with antibacterial rates of 98.30%, 99.36%, and 98.11% against P aeruginosa, S aureus, and E coli, respectively, and can effectively filter airborne bacterial aerosols. Moreover, SA-CPN achieves real-time detection of ammonia concentrations, effectively identifying ammonia levels in exhaled human breath and external environments, and monitoring the human respiratory rate, potentially identifying underlying health conditions. The directional water vapor transmission capability of SA-CPN improves comfort when wearing. Notably, SA-CPN can fully biodegrade within 5 h under enzyme action. The proposed multifunctional electronic mask, featuring biocompatibility, biodegradability, self-disinfection, and ammonia sensing capabilities, holds significant promise in personal medical protective equipment for health monitoring and disease prevention.

Transformative personalized oxalate biomarker analysis through a wrist-worn microneedle device integrated with duplex nanozyme toolbox

The interstitial fluid (ISF) is valuable for disease diagnosis due to its unique biomarkers. Microneedles (MNs) offer a painless method for ISF sampling, facilitating primary diagnostics. This study introduces a minimally invasive, biocompatible MN patch made from a swellable hydrogel of polyvinyl alcohol (PVA) and polyvinyl pyrrolidone (PVP), which effectively extracts ISF. The hydrogel selectively permits small molecules like oxalate, a kidney disease biomarker, while blocking large biomolecules. The MN patch is integrated with a multilayer sensor via microfluidic channels, featuring cotton fiber, agarose, and Mn3[Fe(CN)6]2, alongside Fe3[Fe(CN)6]3 (AGH-CP/MnFeCN/FeFeCN). These nanozymes exhibit oxidase-like activity, reacting with 3,3′,5,5′-tetramethylbenzidine (TMB) to indicate oxalate levels through a color change from green (no oxalate) to light or dark blue, based on concentration. The designed sensor demonstrates high performance with a detection limit of 0.897 μM and an RSD of 1.22 %, enabling accurate quantification via smartphone image analysis as readout platforms for more accessibility and user-friendliness which helps to reach personalized healthcare goals. This integration facilitates real-time, remote, precise disease detection, biochemical analysis and forsooth miniaturization, leading to the development of portable, flexible, and wearable sensors. The MN patch and integrated sensor show excellent stability, selectivity, sensitivity, reliability, and long-term durability. This minimally invasive sensing system, designed for wristband integration, opens new avenues for precision point-of-care monitoring, enhancing personal healthcare.

Tear-Based Ocular Wearable Biosensors for Human Health Monitoring.

Wearable tear-based biosensors have garnered substantial interest for real time monitoring with an emphasis on personalized health care. These biosensors utilize major tear biomarkers such as proteins, lipids, metabolites, and electrolytes for the detection and recording of stable biological signals in a non-invasive manner. The present comprehensive review delves deep into the tear composition along with potential biomarkers that can identify, monitor, and predict certain ocular diseases such as dry eye disease, conjunctivitis, eye-related infections, as well as diabetes mellitus. Recent technologies in tear-based wearable point-of-care medical devices, specifically the state-of-the-art and prospects of glucose, pH, lactate, protein, lipid, and electrolyte sensing from tear are discussed. Finally, the review addresses the existing challenges associated with the widespread application of tear-based sensors, which will pave the way for advanced scientific research and development of such non-invasive health monitoring devices.

Noninvasive Anemia Detection and Prediagnosis

Background Anemia is a significant global health concern, often stemming from iron deficiency or deficiencies in folate, vitamins B12, and A. Anemia disproportionately impacts vulnerable populations like children, adolescent girls, and pregnant or postpartum women. Purpose Anemia is a serious public health issue, impairing productivity, cognitive development, and increasing mortality rates. Anemia is usually detected through blood tests measuring hemoglobin levels, but non-invasive solutions are rquired to lower discomfort, enhance accessibility, and allow for regular monitoring. These methods are essential for early detection in vulnerable populations. Methodology The research methodology involves extracting valuable information from nail images using data mining algorithms. The focus is on calculating the percentage of blue- and red-stained cells within specific regions of interest in the nail images. Machine-learning algorithms are employed to transform these data into actionable insights for disease diagnosis. Results The system demonstrates effectiveness in accurately detecting anemia and providing prediagnosis reports to healthcare providers. The reports include comprehensive information such as patient symptoms, health history, test results, and the doctor’s preliminary assessment. This aids in timely and accurate treatment decisions. Conclusion This research showcases the potential of image processing and machine learning in improving anemia diagnosis and facilitating personalized healthcare interventions.

Towards generative digital twins in biomedical research

Digital twins in biomedical research, i.e. virtual replicas of biological entities such as cells, organs, or entire organisms, hold great potential to advance personalized healthcare. As all biological processes happen in space, there is a growing interest in modeling biological entities within their native context. Leveraging generative artificial intelligence (AI) and high-volume biomedical data profiled with spatial technologies, researchers can recreate spatially-resolved digital representations of a physical entity with high fidelity. In application to biomedical fields such as computational pathology, oncology, and cardiology, these generative digital twins (GDT) thus enable compelling in silico modeling for simulated interventions, facilitating the exploration of ‘what if’ causal scenarios for clinical diagnostics and treatments tailored to individual patients. Here, we outline recent advancements in this novel field and discuss the challenges and future research directions.

Closed-Loop Recycling of Wearable Electronic Textiles.

Wearable electronic textiles (e-textiles) are transforming personalized healthcare through innovative applications. However, integrating electronics into textiles for e-textile manufacturing exacerbates the rapidly growing issues of electronic waste (e-waste) and textile recycling due to the complicated recycling and disposal processes needed for mixed materials, including textile fibers, electronic materials, and components. Here, first closed-loop recycling for wearable e-textiles is reported by incorporating the thermal-pyrolysis of graphene-based e-textiles to convert them into graphene-like electrically conductive recycled powders. A scalable pad-dry coating technique is then used to reproduce graphene-based wearable e-textiles and demonstrate their potential healthcare applications as wearable electrodes for capturing electrocardiogram (ECG) signals and temperature sensors. Additionally, recycled graphene-based textile supercapacitor highlights their potential as sustainable energy storage devices, maintaining notable durability and retaining ≈94% capacitance after 1000 cycles with an areal capacitance of 4.92 mF cm⁻2. Such sustainable closed-loop recycling of e-textiles showcases the potential for their repurposing into multifunctional applications, promoting a circular approach that potentially prevents negative environmental impact and reduces landfill disposal.

Surface-tension-directed gate functionalization in organic electrochemical transistor for wearable sweat lactate monitoring

Wearable sweat lactate detection holds significant potential for applications in healthcare and exercise performance evaluation. Organic electrochemical transistors (OECTs) is emerging as an efficient platform in wearable lactate sensing by integrating an electron transfer interface between the electrode and the bio-catalytic layer. In this study, we demonstrated a wearable OECT designed for dynamic lactate monitoring in sweat through a one-step deposition of gold nanoparticles (Au NPs) on the gate electrode. Utilizing the simple surface-tension-directed deposition strategy, this method ensures a uniform distribution of Au NPs with high catalytic activity, enabling rapid and sensitive lactate signal transition. Herein, the OECT device exhibits a linear detection range for sweat lactate from tens of micromolars to hundreds of millimolars (r² > 0.97), along with high selectivity and long-term stability in human sweat. Furthermore, we successfully employed this flexible OECT sensor for real-time lactate monitoring system during various physical activities, highlighting its potential for non-invasive evaluation of fatigue and exercise performance in athletes. This work provides an easy-to-use prototype for continuous physiological monitoring, enhancing personalized healthcare and training management.

Multi-Omics Analysis Revealed Significant Metabolic Changes in Brain Cancer Cells Treated with Paclitaxel and/or Topotecan

Glioblastoma (GBM) stands as the most common primary malignant brain tumor. Despite the best standard therapies, GBM survivors have a brief survival time, about 24 months on average. The treatment is troublesome because the cancer cells may not respond well to specific therapies as they grow within an extensive network of blood vessels. Our study aims to evaluate the impact of paclitaxel 5.3 μg/mL and topotecan 0.26 μM solely and in pairwise combination on the resultant metabolic and proteomic signatures of the U87 cell line while using the precise ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF) analytical technology. The U87 cells wear treated with DMSO, paclitaxel 5.3 μM, topotecan 0.26 μM, and their combinations. Using One-way ANOVA, we observed 14 significantly altered metabolites compared to those cells treated with DMSO. For combination treatment (paclitaxel and topotecan), 11 metabolites were significantly dysregulated. Sparse partial least squares-discriminant analysis (sPLS-DA) revealed minimal overlap, highlighting distinctions among the four groups. While for proteomics, a total of 79 proteins were significantly dysregulated among the groups. These findings can aid in identifying new biomarkers associated with the utilized drugs and creating a map for targeted therapy. EIF3F, GNB2L1, HINT2, and RPA3 were shown to be significantly upregulated in the combination group relative to the control. Moreover, ribosome, apoptosis, HIF-1 signaling, arginine and proline, glutathione, purine metabolism, apelin signaling pathway, and glycolysis were significantly altered in the combination group. Overall, this study underscores the effectiveness of multi-omics approaches in revealing the molecular mechanisms driving chemotherapy responses in cancer cells. Additionally, this work generates a comprehensive list of molecular alterations that can serve as a foundation for further investigations and inform personalized healthcare strategies to enhance patient outcomes.

Machine learning models for personalised healthcare on marketable generative-AI with ethical implications

Personalised healthcare, underpinned by a deep understanding of individual patient variability, demands innovative solutions. Machine Learning (ML) models offer a promising avenue to achieve this by facilitating the development of enhanced Digital Twins (DTs). This research proposes a novel framework for creating DTs tailored to individual patients, considering not only physical attributes but also the intricate interplay of social, and biological factors. By capturing this comprehensive patient profile, ML-powered DTs have the potential to revolutionise healthcare by enabling predictive, preventive, and personalised care strategies, ultimately leading to improved patient outcomes and the development of a marketable, trust-worthy product. Current healthcare solutions lack personalisation, often failing to consider individual differences in disease presentation and response to treatment. Traditional DTs in healthcare often adopt a disease-centric or organ-specific approach, thereby restricting their capacity to deliver comprehensive, personalised care. To address this limitation, we propose a holistic Artificial Intelligence (AI) framework centered on ML models. Initially focusing on diabetes, our research aims to enhance diagnosis, treatment, and predictive capabilities through personalised insights, thereby optimising patient outcomes and care management. The benefits identified with our ML model are early disease prevention and risk stratification, optimised treatment planning and therapy selection, enhanced patient-physician communication and shared decision-making, reduced healthcare costs and improved resource allocation. Our models are designed to optimise patient care while prioritising safety and societal benefit. To ensure this, we have conducted a thorough assessment of potential ethical implications. Key challenges identified include data privacy and security, algorithmic bias, diagnostic accuracy, data interoperability and standardisation, integration with existing healthcare systems, ethical management of sensitive patient data, refinement of ML methodologies, addressing legal and ethical AI challenges, and suggesting robust ethical guidelines. A comprehensive evaluation of accuracy, reliability, and associated risks will be conducted prior to full-scale integration into the healthcare ecosystem to establish a robust ethical framework for our research models.

Care manager role for older multimorbid heart failure patients' needs in relation to psychological distress and quality of life: a cross-sectional study.

There are few studies investigating patients' needs in healthcare focusing on disease severity and psychological characteristics of elderly heart failure (HF) patients with multimorbidity, specifically addressed by a care manager (CM). To explore the role of a CM dealing with elderly multimorbid HF patients' needs/preferences according to NYHA class, ejection fraction, psychological/psychosomatic distress and quality of life (QoL), utilizing a Blended Collaborative Care (BCC) approach (ESCAPE; Grant agreement No 945377). Cue cards, self-reported questionnaires, and a semi-structured interview were used to collect data. Twenty-five Italian patients (mean age ± SD = 77.5 ± 6.68) were enrolled between June 2021 and March 2022. The most relevant patients' needs to be addressed by a CM were: education (e.g., on medical comorbidities), individual treatment tailoring (e.g., higher number of appointments with cardiologists) and symptom monitoring. The study highlights the importance of targeting HF patients' needs according to psychological characteristics, whose healthcare requires person-centered care with CM assistance. In view of ESCAPE BCC intervention, a CM should consider specific patients' needs of elderly multimorbid HF patients with psychological, psychosomatic distress, particularly somatization, and lower QoL to achieve a more personalized health care pathway. The «Evaluation of a patient-centred biopsychosocial blended collaborative care pathway for the treatment of multi-morbid elderly patients» (ESCAPE) study has been registered at the University of Göttingen Medical Centre (UMG Reg. No 02853) and the German Clinical Trials Register (DRKS00025120).

Advanced Pressure-Sending Wristband for Disease Detection Based on Traditional Chinese Medicine Pulse Diagnosis

This paper explores the integration of Traditional Chinese Medicine (TCM) pulse diagnosis with modern sensor technology to develop a sophisticated wristband system for monitoring vital organ health. Leveraging the principles of TCM, the proposed system focuses on the “Three regions and nine indicators” method to accurately detect pulse variations at different wrist positions and depths. By utilizing a pressure sensor array that covers the Cun, Guan, and Chi pulse positions, the wristband aims to enhance diagnostic accuracy beyond conventional wearable technologies. The system incorporates advanced micro-electro-mechanical techniques to minimize size while maintaining functionality, enabling continuous health monitoring through a coplanar crossed sensing array. Additionally, the use of machine learning algorithms facilitates the analysis of pulse data to identify potential health issues related to the heart, lungs, liver, kidneys, and spleen. An accompanying mobile app provides real-time feedback and health insights, promoting proactive health management. This innovative approach merges TCM’s holistic diagnosis methods with cutting-edge technology to offer a powerful tool for early disease detection and health monitoring, potentially transforming the landscape of personal healthcare devices.