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The Internet of Things (IoT) has emerged as a transformative technology in managing Alzheimer’s Disease (AD), offering novel solutions for early diagnosis, continuous patient monitoring, and assistive care. This review presents a comprehensive analysis of IoT-enabled systems tailored to AD care, focusing on wearable biosensors, cognitive monitoring tools, smart home automation, and Artificial Intelligence (AI)-driven analytics. A systematic literature survey was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify, screen, and synthesize 236 relevant studies primarily published between 2020 and 2025 across IEEE Xplore, PubMed, Scopus and Web of Science. The inclusion criteria targeted peer-reviewed articles that proposed or evaluated IoT-based solutions for AD detection, progression monitoring, or patient assistance. Key findings highlight the effectiveness of the IoT in detecting behavioral and cognitive changes, enhancing safety through real-time alerts, and improving patient autonomy. The review also explores integration challenges such as data privacy, system interoperability, and clinical adoption. The study reveals critical gaps in real-world deployment, clinical validation, and ethical integration of IoT-based systems for Alzheimer’s care. This study aims to serve as a definitive reference for researchers, clinicians, and developers working at the intersection of the IoT and neurodegenerative healthcare.

Herein, a wireless and soft smart contact lens that enables real‐time quantitative recording of cholesterol in tear fluids for the monitoring of patients with hyperlipidemia using a smartphone is reported. This contact lens incorporates an electrochemical biosensor for the continuous detection of cholesterol concentrations, stretchable antenna, and integrated circuits for wireless communication, which makes a smartphone the only device required to operate this lens remotely without obstructing the wearer's vision. The hyperlipidemia rabbit model is utilized to confirm the correlation between cholesterol levels in tear fluid and blood and to confirm the feasibility of this smart contact lens for diagnostic application of cholesterol‐related diseases. Further in vivo tests with human subjects demonstrated its good biocompatibility, wearability, and reliability as a non‐invasive healthcare device. The authors present the soft smart contact lens that can detect cholesterol levels in tear fluids. This smart contact lens consists of an electrochemical cholesterol biosensor, an antenna, and a near‐field communication chip. This device shows stable cholesterol detection and portability. In addition, the cholesterol correlation between tear and blood is confirmed using rabbit models and human studies.

Purpose of ReviewOur day-to-day life is saturated with health data that was previously out of reach. Over the last decade, new devices and fitness technology companies are attempting to tap into this data, uncovering a treasure trove of useful information that, when applied correctly, has the potential to revolutionize the way we approach healthcare and chronic conditions like asthma, especially in the wake of the COVID-19 pandemic.Recent FindingsBy harnessing exciting developments in personalization, digitization, wellness, and patient engagement, care providers can improve health outcomes for our patients in a way we have never been able to do in the past. While new technologies to capture individual health metrics are everywhere, how can we use this information to make a real difference in our patients’ lives? Navigating the complicated landscape of personal wearable devices, asthma inhaler sensors, and exercise apps can be daunting to even the most tech savvy physician.SummaryThis manuscript will give you the tools necessary to make lasting changes in your patients’ lives by exposing them to a world of usable, affordable, and relatable health technology that resonates with their personal fitness and wellness goals. These tools will be even more important post-COVID-19, as the landscape of clinical outpatient care changes from mainly in-person visits to a greater reliance on telemedicine and remote monitoring.

There have been many attempts to predict new markets, including a new market for internet of things (IoT)-based healthcare and the IoT platform’s ability to offer a variety of applications. It is anticipated that the market for these devices will continue to grow as the healthcare sector undergoes fast expansion. IoT can measure a user’s kinetic data (calorie consumption, distance, number of steps, etc.) using wearable healthcare equipment. Most of the recent top research on IoT-based healthcare wearable devices (IWHDs) has, up to this point, concentrated on potential users. The medical industry and healthcare are being quickly changed by the use and adoption of wearable healthcare devices. This study intended to uncover the mediating impacts of “perceived ease of use”, “perceived usefulness”, and “community immersion” on the interactions between influencing factors (personalization, service convenience, interactivity), and the intention to utilize IHWDs. The moderating role of a consumer’s innovativeness in the influence link between IHWD features on perceived ease of use and perceived usefulness was also examined. The study found that personalization has a direct (+) impact on usage intention. Through this, it would be feasible to raise the intention of wearable medical devices being accepted if customized benefits that are thoroughly examined just for individuals are supplied. The association between personalization and continued use intention was shown to be partially mediated by perceived utility and community immersion. Additionally, the association between interactivity and continued use intention, was fully mediated by perceived usefulness and community immersion. By analyzing the elements influencing the usage intention of wearable healthcare devices, this study offers a marketing plan to increase the number of users. The internet of medical things (IoMT) sector has had compound growth of approximately 26% from 2018 to 2021, which is a remarkable accomplishment. The effectiveness of factors affecting IoT usage was examined in this study when applied to the actual IoT industry. First, patients with diabetes who previously had to check their blood sugar levels through a blood test can now check it through lifestyle management and steady glucose monitoring through IoMT glucose monitoring when the convenience and individuality of the service are improved. So far, 10% of all Americans have benefited from this device. Second, as an illustration of interactivity, an IoMT-connected inhaler used to assist asthma sufferers with breathing, notifies the user when the inhaler is left at home and reminds them of appropriate times to use the device. This subsequently resulted in saving 1 life out of every 3 deaths. In addition, the findings of this study may also provide a turning point for the design and development of cutting-edge IoT-based healthcare goods and services.

Herein we describe the use of a new DNAzyme/graphene hybrid material as a biointerfaced sensing platform for optical detection of pathogenic bacteria. The hybrid consists of a colloidal graphene nanomaterial and an Escherichia coli-activated RNA-cleaving DNAzyme and is prepared via non-covalent self-assembly of the DNAzyme onto the graphene surface. Exposure of the hybrid material to E. coli-containing samples results in the release of the DNAzyme, followed by the cleavage-mediated production of a fluorescent signal. Given that specific RNA-cleaving DNAzymes can be created for diverse bacterial pathogens, direct interfacing of graphene materials with such DNAzymes represents a general and attractive approach for real-time, sensitive, and highly selective detection of pathogenic bacteria.

Parenteral artificial nutrition (PAN) is a lifesaving treatment for a large population of patients affected by different diseases, and it consists of intravenous injection of nutritive fluids by means of infusion pumps. Wrong PAN solutions are, unfortunately, often administered, thus threatening the patients’ well-being. Here, we report an optofluidic label-free sensor that can distinguish PAN solutions on the basis of their volumetric refractive index (RI). In our system, a monochromatic light beam, generated by a laser diode, travels obliquely through a transparent, square-section polystyrene channel, is then back-reflected by a mirror, and finally exits the channel in a position that depends on the filling fluid RI. The displacement of the output light spot ΔXexperim is easily detected with a linear, 1-D position sensitive detector (PSD). We initially calibrated the sensor with water-glucose solutions demonstrating a sensitivity S = ΔXexperim/Δn = 13,960 µm/RIU. We then clearly distinguished six commercial PAN solutions, commonly administered to patients. To the best of our knowledge, this is the first reported healthcare sensing platform for remote contactless recognition of PAN fluids, which could be inserted into infusion pumps to improve treatment safety, by checking the compliance to the prescription of the fluid actually delivered to the patient.

This study empirically examined the effects of internal and external factors on actual use behavior, health improvement expectancy, and continuous use intention of healthcare wearable devices. The study proposed a research model with its associated hypotheses that were tested using structural equation modeling. We also performed a comparative analysis of the two sample groups (medical personnel and general public), based on data collected from 288 healthcare wearable devices/apps users. The findings of the study indicated that internal and external factors have positive effects on actual use behavior, and health improvement expectancy and continuous use intention of healthcare wearable devices can be promoted through actual use behavior. The comparative analysis of the two groups showed that medical personnel had higher relationships among the study factors than general public. The study results shed theoretical and practical implications regarding how healthcare wearable devices or apps can be effectively used for disease prevention and health management for the users.

For a fiber‐based strain sensor to be used as a wearable device, its conductivity and sensing characteristics should be stably maintained even during repeated mechanical movements. Additionally, the sensing characteristics should remain unaffected by external contaminants, such as water or sweat, as the sensor is expected to be in contact with the human body. In this study, a superhydrophobic and highly elastic strain‐sensing fiber with durability against continuous tension and contraction while maintaining a stable sensing performance even when in contact with water and sweat is developed. A carbon nanotube is embedded, which is a highly conductive material, inside a spandex fiber with high elasticity and shape recovery rate, enabling the stable measurement of repetitive joint movements under various strain conditions. Furthermore, a superhydrophobic silica aerogel is embedded inside the spandex fiber to facilitate stable sensing without malfunction even when exposed to external contaminants. The proposed strain‐sensing fiber can monitor joints of the human body during various movements, such as dumbbell pressing, squatting, walking, and running. Therefore, the study findings can contribute to the development of wearable healthcare devices that warrant reliable sensing. A superhydrophobic and highly elastic strain‐sensing fiber can withstand continuous tension and contraction while maintaining a stable sensing performance even when in contact with water and sweat. This can be achieved through a simple dipping and drying method, which embeds a carbon nanotube and silica aerogel within a spandex fiber that has a high elasticity and shape recovery rate.

Graphene-based electronic DNA sequencing techniques have received significant attention over the past decade and are hoped to provide a new generation of portable, low-cost devices capable of rapid and accurate DNA sequencing. However, these devices are yet to demonstrate DNA sequencing. This is partly due to complex fabrication requirements resulting in low device yields and limited throughput. In this paper, we review the challenging fabrication of graphene-based electronic DNA sequencing devices. We will place a particular focus on common fabrication challenges and look toward the development of high-throughput, high-yield fabrication of these devices.

Continuous monitoring of pacemaker activity can provide valuable information to improve patients’ follow-up. Concise information is stored in some types of pacemakers, whereas ECG can provide more detailed information, but requires electrodes and cannot be used for continuous monitoring. This study highlights the possibility of a continuous monitoring of pacemaker pulses by sensing magnetic field variations due to the current pulses. This can be achieved by means of a sensor coil positioned near the patient’s thorax without any need for physical contact. A simplified model of coil response to pacemaker pulses is presented in this paper, along with circuits suitable for pulse detection. In vitro tests were carried out using real pacemakers immersed in saline solution; experimental data were used to assess the accuracy of the model and to evaluate the sensor performance. It was found that the coil signal amplitude decreases with increasing distance from the pacemaker lead wire. The sensor was able to easily perform pacemaker spike detection up to a distance of 12 cm from the pacemaker leads. The stimulation rate can be measured in real time with high accuracy. Since any electromagnetic pulse triggers the same coil response, EMI may corrupt sensor measurements and thus should be discriminated.