Heart Rate Sensor Research Articles

Internet based highly secure data transmission system in health care monitoring system

<span>The health care systems in our contemporary countries are advancing rapidly in terms of maturity and professionalism. In an effort to alleviate the current burden on the public health system and boost the popularity of regular health self-checks, this method has been developed for producing prediagnoses that are easier to use, quicker, and more accurate. To ascertain how well the heart is circulating oxygen throughout the body, a pulse test, a painless examination that measures an individual's degree of oxygen saturation, is used. It can be used to evaluate the state of any patient with a disease, particularly those with pulmonary problems. Diseases in these patients could need ongoing observation and care. Our system comes to the rescue in order to resolve this problem. This portable system is simple to use and may be taken anywhere by the subject. The internet of things (IoT) will update the pertinent parameters. This health monitoring system's controller is made up of an adaptor, a saturation of peripheral oxygen (SPO2 ) sensor (a blood oxygen meter), a temperature sensor, a heart rate sensor, a WiFi module, and a liquid crystal display (LCD).</span>

Pilot turning behavior cognitive load analysis in simulated flight.

To identify the cognitive load of different turning tasks in simulated flight, a flight experiment was designed based on real "preliminary screening" training modules for pilots. Heart Rate Variability (HRV) and flight data were collected during the experiments using a flight simulator and a heart rate sensor bracelet. The turning behaviors in flight were classified into climbing turns, descending turns, and level flight turns. A recognition model for the cognitive load associated with these turning behaviors was developed using machine learning and deep learning algorithms. pnni_20, range_nni, rmssd, sdsd, nni_20, sd1, triangular_index indicators are negatively correlated with different turning load. The LSTM-Attention model excelled in recognizing turning tasks with varying cognitive load, achieving an F1 score of 0.9491. Specific HRV characteristics can be used to analyze cognitive load in different turn-ing tasks, and the LSTM-Attention model can provide references for future studies on the selection characteristics of pilot cognitive load, and offer guidance for pilot training, thus having significant implications for pilot training and flight safety.

Dynamically crosslinked poly(vinyl alcohol)/borax strain sensors for organ motion monitoring

Wearable electronic sensing devices can detect various physiological responses and subtle changes in the skin in real time for the early detection and treatment of potential health problems or diseases. Among them, flexible hydrogel-based sensors are attracting much attention because they can monitor human movements and physiological signals. However, developing hydrogel-based sensors with rapid self-healing, self-adhesion, excellent conductivity and sensitivity characteristics remains a challenge. In this study, a hydrogel with a dynamic reversible network structure was developed using poly(vinyl alcohol) (PVA), hyaluronic acid (HA), borax, and tannic acid (TA). Multiple hydrogen bonds resulting from abundant hydroxyl groups in the hydrogel composed of borax, PVA, and TA improved the self-healing ability of the hydrogel, and the conductivity of this system (∼0.62 S/m) was improved upon immersion in NaCl. The optimum hydrogel exhibited excellent elasticity (∼941 %), biocompatibility, and demonstrated adhesion to porcine skin (dry: 5.3 kPa; wet: 2 kPa) without external stimulation in air and underwater environments. In addition, the fabricated hydrogels exhibited excellent sensitivity (∼300 % strain, gauge factor (GF) = 2.86; 300–900 % strain, GF = 4.95), allowing them to detect and distinguish various large and small human movements. Hydrogels that exhibited stable electrical signals even after 500 cycles were obtained, and the PBHT-N hydrogels were implanted into rabbit hearts to verify their applicability as strain sensors for effective real-time heart rate monitoring during rapid body movement.

Impact of a Precision Intervention for Vascular Health in Middle-Aged and Older Postmenopausal Women Using Polar Heart Rate Sensors: A 24-Week RCT Study Based on the New Compilation of Tai Chi (Bafa Wubu).

(1) Background: This study utilized a 24-week intervention incorporating heart rate sensors for real-time monitoring of intervention training, aiming to comprehensively assess the effects of Tai Chi on vascular endothelial function, atherosclerosis progression, and lipid metabolism. The insights gained may inform personalized non-pharmacological interventions to enhance the management of cardiovascular health in this population to provide sustainable benefits and improve quality of life. (2) Methods: Forty postmenopausal middle-aged and elderly women were randomly assigned to an exercise or control group. The exercise group underwent a 24-week Tai Chi (BaFa WuBu) training intervention with real-time heart rate monitoring using Polar sensors. Pre- and post-intervention assessments included body composition, blood pressure, vascularity, and blood parameters measured with the Inbody 720, Vascular Endothelial Function Detector, and Arteriosclerosis. Data were analyzed using SPSS 26.0 and mixed-design ANOVA to assess the effects of time, group, and their interactions on study outcomes. (3) Results: After training through 24 weeks of Tai Chi (BaFa WuBu) intervention, compared with the control group, systolic blood pressure in the exercise group was significantly lower (p < 0.05), and the difference between left and right arm pulse pressure, left and right ankle mean arterial pressure, left and right side baPWV, left and right side ABI, TC, TG, LDL, and blood pressure viscosity were all very significantly lower (p < 0.01), and the diastolic blood pressure was significantly higher (p < 0.05). Compared with baseline values in the exercise group, systolic blood pressure, right and left arm pulse pressure difference, right and left ankle mean arterial pressure, right and left side baPWV, right and left side ABI, TC, TG, LDL, and blood pressure viscosity decreased very significantly (p < 0.01) and diastolic blood pressure and FMD increased very significantly (p < 0.01) in the exercise group after the intervention. (4) Conclusions: In our study, a 24-week Tai Chi (BaFa WuBu) program significantly improved vascular health in middle-aged and older postmenopausal women. This simplified Tai Chi form is gentle and effective, ideal for older adults. Regular practice led to reduced vascular obstruction, improved lipid metabolism, and enhanced vascular endothelial function, crucial for preventing vascular diseases. The real-time heart rate sensors used were pivotal, enabling precise monitoring and adjustment of exercise intensity, thereby enhancing the study's scientific rigor and supporting Tai Chi (BaFa WuBu) as a beneficial therapeutic exercise.

Application of Industry 4.0 and digital twin in the field of smart healthcare

There is an increasing need for preventive health care as well as precise diagnosis and tailored treatment of different diseases in recent years. Providing customized treatment for each patient and maximizing accuracy and efficiency are main goals of a good healthcare system. This thesis explores the integration of digital twin technology with Industry 4.0 in healthcare. Digital twins create virtual representations of physical systems, enabling real-time monitoring and tailored treatments. Key elements include the living human body, IoT, digital twin, cloud computing, and simulation. The architecture comprises data acquisition, data munging, data storage, data simulation with analytics, and user access layers. Creating a digital twin involves precise 3D modeling, representing the entire body or specific organs. A case study demonstrates real-time monitoring using wearable sensors for blood pressure, blood sugar, and heart rate. Data is transmitted, integrated with the digital twin, and accessible via a website with alarms for abnormal readings. While Industry 4.0 and digital twin adoption in healthcare is evolving, the architecture serves as a reference. It offers real-time data for diagnosis and treatment, with potential for advanced simulations. Challenges include automated data systems and privacy concerns. Despite limitations, this integration holds promise for precision medicine and personalized healthcare.

Do Different Playing Formats and Aerobic Capacity Influence Variances in Psychophysiological Demands and Technical Performance in Small-Sided Games? A Study among Under-17 Male Soccer Players.

This study aimed to: (i) analyze the variations in psychophysiological demands (mean heart rate, meanHR; rate of perceived exertion, RPE) and technical performance (umber of successful and unsuccessful passes, and occurrences of ball loss) between 2v2 and 4v4 small-sided games (SSGs) formats, and (ii) examine the relationships of aerobic capacity measured in Yo-Yo Intermittent Recovery Test (YYIRT) on psychophysiological and technical performance during SSGs. This study used a cross-sectional design with repeated measures, where the same players participated in both 2v2 and 4v4 formats across two training sessions per format. Twenty-four talent/developmental male youth soccer players, aged 16.6 ± 0.5 years. The meanHR, measured through heart rate sensors, the RPE, assessed using the CR6-20 scale, and the number of successful and unsuccessful passes, along with occurrences of ball loss, recorded using an ad hoc observational tool, were evaluated in each repetition. Players during the 2v2 format had significantly greater mean HR (+4.1%; p < 0.001; d = 2.258), RPE (+12.2%; p < 0.001; d = 2.258), successful passes (+22.2%; p = 0.006; d = 0.884), unsuccessful passes (+62.5%; p < 0.001; d = 1.197) and lost balls (+111.1%; p < 0.001; d = 2.085) than 4v4 format. The YYIRT was significantly and largely correlated with unsuccessful passes (r = 0.502; p = 0.012) and lost balls (r = 0.421; p = 0.041) in 2v2 format. In conclusion, this study suggests that engaging in 2v2 activities constitutes a more intense form of practice, significantly enhancing individual participation in technical aspects. Moreover, aerobic capacity may influence the smaller formats of play and how players perform key technical actions. Therefore, coaches must consider this to ensure the necessary performance in such games.

Developing a Mobile Application for IoT-Powered Health Monitoring Systems

A multidisciplinary approach is typically required to address health issues effectively in medical emergencies. Traditional sensor-based diagnostics in healthcare, when applied on a large scale, demand numerous sensors and significant human intervention. To address these challenges, this research proposes an IoT-based healthcare application designed to streamline patient monitoring. The system is built around an online mobile application that enables continuous, wireless observation of patients' health. The primary objective is to develop a cost-effective solution that transmits vital patient parameters during emergencies. Sensors such as ECG monitors, heart rate sensors, and temperature sensors are employed to measure critical health indicators. The collected data is transmitted to the cloud via a microcontroller-connected module for storage on an IoT platform. In the cloud, the data is processed, and relevant feedback is generated, allowing doctors to assess the patient's condition remotely. This remote monitoring reduces the workload on healthcare professionals while ensuring accurate patient health assessments. In cases requiring urgent attention, alerts are sent to caregivers or doctors. This system aids in early intervention and enhances the quality of patient care. The proposed setup has been validated through simulations and various test experiments.

Combined Impact of Heart Rate Sensor Placements with Respiratory Rate and Minute Ventilation on Oxygen Uptake Prediction.

Oxygen uptake (V˙O2) is an essential metric for evaluating cardiopulmonary health and athletic performance, which can barely be directly measured. Heart rate (HR) is a prominent physiological indicator correlated with V˙O2 and is often used for indirect V˙O2 prediction. This study investigates the impact of HR placement on V˙O2 prediction accuracy by analyzing HR data combined with the respiratory rate (RESP) and minute ventilation (V˙E) from three anatomical locations: the chest; arm; and wrist. Twenty-eight healthy adults participated in incremental and constant workload cycling tests at various intensities. Data on V˙O2, RESP, V˙E, and HR were collected and used to develop a neural network model for V˙O2 prediction. The influence of HR position on prediction accuracy was assessed via Bland-Altman plots, and model performance was evaluated by mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE). Our findings indicate that HR combined with RESP and V˙E (V˙O2HR+RESP+V˙E) produces the most accurate V˙O2 predictions (MAE: 165 mL/min, R2: 0.87, MAPE: 15.91%). Notably, as exercise intensity increases, the accuracy of V˙O2 prediction decreases, particularly within high-intensity exercise. The substitution of HR with different anatomical sites significantly impacts V˙O2 prediction accuracy, with wrist placement showing a more profound effect compared to arm placement. In conclusion, this study underscores the importance of considering HR placement in V˙O2 prediction models, with RESP and V˙E serving as effective compensatory factors. These findings contribute to refining indirect V˙O2 estimation methods, enhancing their predictive capabilities across different exercise intensities and anatomical placements.

Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data

Visually Impaired People (VIP) face significant challenges in their daily lives, relying on others or trained dogs for assistance when navigating outdoors. Researchers have developed the Smart Stick (SS) system as a more effective aid than traditional ones to address these challenges. Developing and utilizing the SS systems for VIP improves mobility, reliability, safety, and accessibility. These systems help users by identifying obstacles and hazards, keeping VIP safe and efficient. This paper presents the design and real-world implementation of an SS using an Arduino Nano microcontroller, GPS, GSM module, heart rate sensor, ultrasonic sensor, moisture sensor, vibration motor, and Buzzer. Based on sensor data, the SS can provide warning signals to VIP about the presence of obstacles and hazards around them. Several Machine Learning (ML) algorithms were used to improve the SS alert decision accuracy. Therefore, this paper used sensor data to train and test ten ML algorithms to find the most effective alert decision accuracy. Based on the ML algorithms, the alert decision, including the presence of obstacles, environmental conditions, and user health conditions, was examined using several performance metrics. Results showed that the AdaBoost, Gradient boosting, and Random Forest ML algorithms outperformed others and achieved an AUC and specificity of 100%, with 99.9% accuracy, F1-score, precision, recall, and MCC in the cross-validation phase. Integrating sensor data with ML algorithms revealed that the SS enables VIP to live independently and move safely without assistance.

Wearable heart rate sensing and critical power-based whole-body fatigue monitoring in the field

Whole-body fatigue (WBF) presents a concerning risk to construction workers, which can impact function and ultimately lead to accidents and diminished productivity. This study proposes a new WBF monitoring technique by applying the Critical Power (CP) model, a bioenergetic model, with a wrist-worn heart rate sensor. The authors modified the CP model to calculate WBF from the percentage of heart rate reserve (%HRR) and generated a personalized model via WBF perception surveys. Data were collected for two days from 33 workers at four construction sites. The results showed that the proposed technique can monitor field workers’ perceived WBF with a mean absolute error of 12.8% and Spearman correlation coefficient of 0.83. This study, therefore, demonstrates the viability of wearable WBF monitoring on construction sites to support programs aimed at improving workplace safety and productivity.

Enhancing stress assessment in sledge reindeer (Rangifer tarandus): a pilot study on infrared thermal imaging and its opportunities for advancement as a welfare assessment tool

Measuring immediate physiological stress responses in animals can be challenging; saliva and blood sampling, while invasive, may also generate confounding stress responses, and equipping animals with heart rate sensors is not always feasible. Nevertheless, emerging technologies offer a non-invasive and contactless method to measure additional body surface temperature changes induced by acute stress, using infrared thermal measurement of the eye caruncle region. Contactless temperature measurement has the potential to assess the emotional state of animals affected by human physical contact. Reindeer, being highly sensitive to touch and naturally avoiding physical contact, exemplify this case. With growing interest in safari tours involving sledging reindeer, there is a need to investigate how these animals are affected by human interactions and how they adapt to daily close contact. In this pilot experiment, we evaluated the efficacy of thermal imaging in measuring medial canthus temperature fluctuations in non-habituated sledging reindeer while being petted by unfamiliar humans. Our findings support the hypothesis that medial canthus temperature significantly decreases during petting and increases once the interaction ceases, aligning with established stress response patterns found in the literature. This pilot experiment underscores the potential of infrared thermal imaging for non-invasively monitoring physiological responses to stress in tamed reindeer. Moreover, it sets the foundation for refining methodologies and experimental designs using infrared thermal imaging in animal welfare research.

Rhodiola Rosea: a plant from the Crassulaceae family that has the potential to reduce muscle pain and increase range of motion during exercise-induced muscle damage

This study aims to analyze the potential of rhodiola rosea in reducing muscle pain and increasing ROM during EIMD. This experimental research uses a pre- and post-control group design. Research subjects were selected using a purposive sampling technique, then the subjects were divided into 2 groups, namely group (K1) which was given placebo and group (K2) which was given rhodiola rosea at a dose of 500 mg. A total of 18 healthy men aged between 19-25 years participated in this study. Data collection began on the first day by collecting data on subject characteristics. After that, they were asked to warm up. Physical activity is carried out afterward. These activities include high-intensity activities, such as walking lunges, good mornings, and leg extensions. This exercise is done in 4 sets with a 1-minute break (recovery) between sets. Exercise intensity is monitored using a Polar H9 Heart Rate Sensor. On day 2 or 24 hours after training, subjects took pre-test data to measure muscle soreness and ROM. Subjects were then given placebo or rhodiola rosea treatment, depending on the group assigned. On the 3rd day or 48 hours after training, post-test data was collected again. Muscle intensity was measured using a Visual Analog Scale (VAS) and ROM was measured at the knee joint using a goniometer. After the data was obtained, the data were analyzed using the IBM SPSS version 26 application. The results of this study reported that the K1 group given placebo did not significantly reduce muscle pain and increase ROM during EIMD, while the K2 group given rhodiola rosea at a dose of 500 mg significantly reduced pain. muscle and increase ROM during EIMD. Considering that pain management and ROM are very necessary to support body function, we recommend the use of rhodiola rosea for sports enthusiasts to support physical performance. Keywords: Rhodiola Rosea, Muscle Pain, Range of Motion, Exercise-Induced Muscle Damage, Inflammation, Healthy lifestyle

Multi-Objective Technology-Based Approach to Home Healthcare Routing Problem Considering Sustainability Aspects

Background: This research aims to solve a home healthcare vehicle routing problem (HHCVRP) model that considers the social aspect of sustainability and will be implemented in smart cities. In addition to the dynamism and uncertainty caused by variations in the patient’s condition, the proposed model considers parameters and variables that enhance its practicability, such as assuming different levels of patient importance (priority). Methods: The model was solved using a metaheuristic algorithm approach via the Ant Colony Optimization algorithm and the Non-Dominated Sorting technique due to the ability of such a combination to work out with dynamic models with uncertainties and multi-objectives. Results: This study proposes a novel mathematical model by integrating body sensors on patients to keep updating their conditions and prioritizing critical conditions in service. The sensitivity analysis demonstrates that using a heart rate sensor improves service quality and patient satisfaction without affecting the energy consumed. In addition, quality costs are increased if the importance levels of patients increase. Conclusions: The suggested model can assist healthcare practitioners in tracking patients’ health conditions to improve the quality of service and manage workload effectively. A trade-off between patient satisfaction and service provider satisfaction should be maintained.

Acute effects of fast, slow, and graded Suryanamaskar on cardiorespiratory and cardiac autonomic functions

BackgroundSuryanamaskar (SN) is a popular yogic practice due to its health benefits and fitness promises. This study aims to assess the acute effects of different paces of SN on cardiorespiratory responses and heart rate variability (HRV). MethodsIn this self-as-control comparative study, seventeen male yoga practitioners performed three rounds of SN at fast (FSN), slow (SSN), and graded (GSN) pace in a randomly allocated sequence. Cardiorespiratory responses and HRV kinetics were continuously monitored using a metabolic gas analyzer and heart rate sensor, respectively, and were analyzed by repeated-measures ANOVA and paired t-test. ResultsFSN involved the highest VO2, followed by GSN and SSN. Average HR (AHR) was significantly greater during FSN compared to SSN (p < 0.01; d = 0.81) and GSN (p < 0.05; d = 0.39). GSN demanded significantly higher (p < 0.05; d = 0.41) stroke volume compared to FSN. VO2, AHR, and energy expenditure (EE) showed a gradual increase across rounds in FSN and SSN, whereas in GSN those significantly reduced. SSN showed significantly lesser EE, fat% utilization, and METS as compared to FSN (p < 0.001) and GSN (p < 0.01). SSN also showed significantly reduced LF power (p < 0.01; d = 0.67), LF/HF ratio, and higher HF power than GSN and FSN. ConclusionFSN is more metabolically demanding compared to the other two paces. SSN is more effective in bringing a state of parasympathetic dominance and GSN brings progressive relaxation. The results provide insights into the acute HRV and cardio-metabolic responses to different SN paces suggesting its potential as a complementary therapy and to promote holistic health and well-being.

The Use of Virtual Reality in Stable Sitting Trunk Rehabilitation for Stroke Patients: A Pilot Study

INTRODUCTION: Virtual reality (VR) holds promise for stroke rehabilitation. However, many existing VR systems requires users to stand while playing, posing a potential falling risk for stroke patients. This study investigated the effects of a custom-developed VR system that focus on trunk rehabilitation in stable sitting position on muscle activities, postural control, and physiological cost compared to conventional trunk exercises in stroke patients. MATERIALS AND METHODS: A cross-sectional observational pilot study was conducted involving 12 paretic stroke subjects performing four exercises: two Conventional Trunk Exercises (CTE) and two VR-based Trunk Exercises (VRTE) using customized Tilt-The-Maze (self-paced) or Catch-The-Mole (game-paced) games. Muscle activity was measured using electromyography (EMG). Postural control data in the Anterior-Posterior (AP) and Medio-Lateral (ML) axes was recorded using a force plate, while the physiological cost was measured via a heart rate sensor during the exercises. RESULTS: The results indicated low muscle activity and light-intensity cardiovascular responses in all CTE and VRTE exercises. Game-paced VRTE recorded slightly higher Center of Pressure (CoP) velocity in the AP and ML axes versus CTE (AP:4.40±1.80 vs. 4.02±1.20 cm/s; ML:6.40±2.54 vs. 5.42±2.21 cm/s). In contrast, the self-paced VRTE showed an insignificant impact on postural control than both CTE and game-paced VRTE. CONCLUSION: The game-paced VRTE induced comparable effects on muscular activation, postural control, and physiological cost to that of CTE in stroke patients. The findings suggest the stable-sitting VR system as a supplementary approach to the existing trunk rehabilitation protocols for stroke patients.

Monitoring Within-Individual Dose-Response Relationships in Professional Soccer Players: The Importance of Fitness Level.

To (1)examine within-individual player dose-response associations between selected training-load measures and changes in aerobic fitness level via submaximal exercise heart rate (HRex%) and (2)measure the relationships between these dose-response associations with basal HRex% (to study the influence of fitness level on dose-response relationship). During an in-season phase, selected training-load measures including total minutes, total distance, mechanical work (the sum number of accelerations and decelerations > 3m2), high metabolic load distance, and Edwards' training impulse were collected via Global Positioning System and heart-rate sensors for analyzing accumulated load. A submaximal warm-up test was used repeatedly before and after 9 phases to elicit HRex% and track fitness changes at an individual level. Negative to positive extensive ranges of within-individual associations were found among players for different metrics (r = -.84 to .89). The relationship between pooled HRex% (basal fitness) and dose-response correlations showed inverse very large (r = -.71) and large (r = -.65) values for accumulated weekly minutes and distance. However, moderate values were found for all other measures (r = -.35 to -.42). Individual players show extensive different ranges of dose-response associations with training measures. The dose-response association is influenced by players' fitness level, and players with lower fitness levels show stronger inverse relationships with accumulated minutes and total distance.

Desain dan Fabrikasi Printed Circuit Board (PCB) Smartband untuk Mengukur Tanda Vital Pada Tubuh Manusia

This research addresses the design and fabrication of a Printed Circuit Board (PCB) for a smartband used to measure vital signs on the human body, including heart rate and body temperature. The main objective of this research is to produce a reliable and accurate device in daily health monitoring. The research process includes system design, design validation, PCB fabrication, component assembly, and testing and calibration. Key components, including heart rate and temperature sensors, were selected and integrated using PCB design software. PCB fabrication was performed through photolithography, etching, drilling, and plating processes. The test results show that the designed PCB meets the expected technical specifications.

IoT Based Medical Assessor and Predictor for HealthCare Solutions

Abstract: The introduction of cutting-edge, intelligent medical equipment into the virtual doctor system is orchestrating a remarkable transformation within community healthcare. Research in the healthcare sector has unveiled promising developments in extending human lifespan. However, obtaining healthcare services in remote areas remains a formidable challenge as patients often have to endure long journeys for treatment. The incorporation of IoT technology offers a viable solution by allowing real-time monitoring of vital signs through sensors like heart rate, Spo2, temperature, B.P and ECG sensors, measuring pulse rate, blood oxygen levels, body temperature, and blood pressure, respectively and applying different machine learning algorithms to predict the condition of the patient and suggest some precautions &amp; medications. The reliability of the collected data is assured, and ThingSpeak software transmits this data to the cloud, enabling the delivery of professional healthcare services to those in need. Notably, statistics reveal that in India, the doctor-to-patient ratio stands at 1:854, underscoring the crucial role of this technology in addressing healthcare requirements in rural communities.

Designing a Care System based on the Internet of Things for Patients with Multiple Sclerosis

Abstract: Multiple sclerosis (MS) is a neurodegenerative disease that is a major health problem. This issue requires the development of new tools to control patients' activity and reduce care costs. The monitoring system based on the Internet of things is a suitable solution for this concern. In this study, the researchers developed a tool that uses an Arduino board and four accelerometer sensors, heart rate and pulse oximetry sensors, temperature sensors, and Bluetooth modules to monitor the factors related to the health of multiple sclerosis patients. In this method, the information obtained from the sensors connected to the patient's body is placed on the memory board and displayed with the help of an LCD. In the next step, the Bluetooth module transmits the information obtained from these sensors to a mobile application. This application has the ability to share and store information. This information, together with the date display on the LCD, in addition to notifying the person of the resulting changes; it is also sent periodically to the doctor. In general, this tool, together with a mobile device, helps to increase the selfcare of patients, increases the interaction between the patient and the doctor, reduces the frequeI. nt visits of patients to care centers, and helps to improve the quality of life of patients..

Alzheimer's Patient Support System Based on IoT and ML

Alzheimer's disease poses significant challenges as it progressively erodes memory and identity, severely impacting daily functioning. Patients often experience disorientation, wandering, and are at risk of falls, leading to heightened concerns for caregivers. These difficulties can result in a loss of independence and increased caregiver burden. In response to these challenges, this study introduces an innovative assistive system designed to enhance the safety and quality of life for Alzheimer's patients. The system comprises of two main components: a smart arm band and a facial recognition system. The smart arm band is equipped with a suite of sensors including GPS, accelerometer, and heart rate sensor. These sensors enable real-time monitoring of the patient's location, movement, and physiological parameters. By leveraging these data streams, caregivers can track the patient's activities, detect falls or emergencies, and provide timely assistance when needed. The facial recognition system employs state-of-the-art machine learning techniques, specifically the CAFFE and Local Binary Patterns Histograms (LBPH), to recognize familiar faces in the patient's environment. This capability promotes social interaction and enhances the patient's sense of familiarity and security. Through rigorous testing, the facial recognition system achieves an impressive accuracy of 97% with a low error rate of 3%, validating its effectiveness in real-world scenarios. Overall, the integrative assistive system presented in this study offers a promising solution to address the multifaceted challenges associated with Alzheimer's disease. This system provides caregivers with invaluable support in ensuring the safety and well-being of Alzheimer's patients while fostering social engagement and autonomy.