Statistical Review of Health Monitoring Models for Real-Time Hospital Scenarios

Health Monitoring System Models (HMSMs) need speed, efficiency, and security to work. Cascading components ensure data collection, storage, communication, retrieval, and privacy in these models. Researchers propose many methods to design such models, varying in scalability, multidomain efficiency, flexibility, usage and deployment, computational complexity, cost of deployment, security level, feature usability, and other performance metrics. Thus, HMSM designers struggle to find the best models for their application-specific deployments. They must test and validate different models, which increases design time and cost, affecting deployment feasibility. This article discusses secure HMSMs' application-specific advantages, feature-specific limitations, context-specific nuances, and deployment-specific future research scopes to reduce model selection ambiguity. The models based on the Internet of Things (IoT), Machine Learning Models (MLMs), Blockchain Models, Hashing Methods, Encryption Methods, Distributed Computing Configurations, and Bioinspired Models have better Quality of Service (QoS) and security than their counterparts. Researchers can find application-specific models. This article compares the above models in deployment cost, attack mitigation performance, scalability, computational complexity, and monitoring applicability. This comparative analysis helps readers choose HMSMs for context-specific application deployments. This article also devises performance measuring metrics called Health Monitoring Model Metrics (HM3) to compare the performance of various models based on accuracy, precision, delay, scalability, computational complexity, energy consumption, and security

ANALYSIS AND DESIGN ANDROID-BASED RESPIRATION RATE MONITORING FOR CLASSIFICATION OF RESPIRATION DISORDERS

Sistem pengawasan pasien rumah sakit yang dilakukan selama ini kebanyakan masih dilakukan secara konvensional yakni dengan sistem mengunjungi pasien berjadwal. Alat pengawasan kondisi pasien tersimpan di dalam ruangan dan bisa dicek hanya saat berada dalam ruangan tersebut. Remote Patient Monitoring (RPM) adalah solusi pemanfaatan teknologi dalam bidang kesehatan yang memungkinkan pasien termonitor secara realtime dan dapat diakses kapan saja. Dalam memonitoring kondisi pasien, salah satu yang perlu terus dipantau adalah respiration rate. Respiration rate ini merupakah salah satu parameter yang paling penting dalam memonitoring pasien karena menjadi penanda kondisi patologis pasien. Dalam pengawasan pasien yang disebut sebagai ABCD Sekunder salah satunya parameter yang menjadi perhatian adalah pernafasan. Melalui tulisan ini telah dibuat suatu perangkat respiration rate monitoring yang dapat diakses secara real time untuk mengimplementasikan konsep RPM. Terdapat juga tambahan fitur yakni perangkat dapat melaporkan hasil monitoring secara detail kondisi normal atau tidaknya respirasi pasien. Perangkat monitoring respirasi yang telah dibuat ini dapat di akses secara real time dengan memanfaatkan jaringan wifi kemudian diterima pada perangkat smartphone sehingga tetap bisa diketahui kondisinya meski tidak berada dalam ruang pasien sekalipun. Data monitoring dapat dilihat lewat visualiasi grafik di smartphone selanjutnya klasifikasi kondisi pasien berdasarkan dari nilai respiration rate yang dihitung. Sistem yang telah dirancang memiliki keakuratan 95,16%. Threshold yang digunakan adalah 27 yang merupakan representasi dari nilai analog sinyal dari sensor. Sistem monitoring respiration rate ini diharapkan dapat digunakan dan dikembangkan untuk membantu dalam memberikan pelayanan yang optimal terutama dalam hal monitoring kondisi pasien

An Artificial Intelligence application for drone-assisted 5G remote e-Health

Artificial intelligence (AI) algorithms are experiencing growing research interest due to their ability to improve decision making capabilities for promising applications in different economic sectors. The growing shift toward the Internet of Everything environments brought by devices embedded with sensors that can share information brings immense opportunity for new applications (apps). While these new apps thrive in resource-rich areas (i.e., capitals), neighboring cities that lack the resources and infrastructure to support them may be left behind. It is vital that new technologies can reach those who need them the most, especially healthcare-based. This article proposes an app-based approach for long-distance patient monitoring and care. The app would serve as a platform of communication between patients and healthcare staff, where the latter can send standardized video footage or pictures to the former (e.g., their primary care doctor). This feature is enhanced with a recurrent neural network algorithm as a validation tool for healthcare-related videos exchanged between patients and staff. Thus, the healthcare team does not need to check each video for validity, freeing their time for other activities

Review on Lightweight Cryptography Techniques and Steganography Techniques for IOT Environment

In the modern world, technology has connected to our day-to-day life in different forms. The Internet of Things (IoT) has become an innovative criterion for mass implementations and a part of daily life. However, this rapid growth leads the huge traffic and security problems. There are several challenges arise while deploying IoT. The most common challenges are privacy and security during data transmission. To address these issues, various lightweight cryptography and steganography techniques were introduced. These techniques are helpful in securing the data over the IoT. The hybrid of cryptography and steganography mechanisms provides enhanced security to confidential messages. Any messages can be secured by cryptography or by embedding the messages into any media files, including text, audio, image, and video, using steganography. Hence, this article has provided a detailed review of efficient, lightweight security solutions based on cryptography and steganography and their function over IoT applications. The objective of the paper is to study and analyze various Light weight cryptography techniques and Steganography techniques for IoT. A few works of literature were reviewed in addition to their merits and limitations. Furthermore, the common problems in the reviewed techniques are explained in the discussion section with their parametric comparison. Finally, the future scope to improve IoT security solutions based on lightweight cryptography and steganography is mentioned in the conclusion part