This work addresses the critical need for secure and patient-controlled Electronic Health Records (EHR) migration among healthcare hospitals’ cloud servers (HHS). The relevant approaches often lack robust access control and leave data vulnerable during transfer. Our proposed scheme empowers patients to delegate EHR migration to a trusted Third-Party Hospital (TTPH); which is the Certification Authority (CA) while enforcing access control. The system leverages asymmetric encryption utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA), EEC and ECDSA added robust security and lightness EHR sharing. Patient and user privacy is managed due to anonymity through cryptographic hashing for data protection and utilizes mutual authentication for secure communication. Formal security analysis using the Scyther tool and informal analysis was conducted to validate the system’s robustness. The proposed scheme achieved EHR integrity due to the verification of the communicated HHS and ensuring the integrity of the HHS digital certificate during EHR migration. Ultimately, the result achieved in the proposed work demonstrated the scheme’s high balance between data security and accuracy of communication, where the best result obtained represented 7.7/ ms as computational cost and 1248 /bits as communication cost compared with the relevant approaches.
The monitoring of COVID-19 patients has been greatly aided by the Internet of Things (IoT). Vital signs, symptoms, and mobility data can be gathered and analyzed by IoT devices, including wearables, sensors, and cameras. This information can be utilized to spot early infection symptoms, monitor the illness’s development, and stop the virus from spreading. It’s critical to take vital signs of hospitalized patients in order to assess their health. Although early warning scores are often calculated three times a day, they might not indicate decompensation symptoms right away. Death rates are higher when deterioration is not properly diagnosed. By employing wearable technology, these ongoing assessments may be able to spot clinical deterioration early and facilitate prompt therapies. This research describes the use of Internet of Things (IoT) to follow fatal events in high-risk COVID-19 patients. These patients’ vital signs, which include blood pressure, heart rate, respiration rate, blood oxygen level, and fever, are taken and fed to a central server on a regular basis so that information may be processed, stored, and published instantly. After processing, the data is utilized to monitor the patients’ condition and send Short Message Service (SMS) alerts when the patients’ vital signs rise above predetermined thresholds. The system’s design, which is based on two ESP32 controllers, sensors for the vital signs listed above, and a gateway, provides real-time reports, high-risk alerts, and patient status information. Clinicians, the patient’s family, or any other authorized person can keep an eye on and follow the patient’s status at any time and from any location. The main contribution in this work is the designed algorithm used in the gateway and the manner in which this gateway collects, analyze, process, and send the patient’s data to the IoT server from one side and the manner in which the gateway deals with the IoT server in the other side. The proposed method leads to reduce the cost and the time the system it takes to get the patient’s status report.
This work concerns creating a monitoring system for a smart hospital using Raspberry Pi to measure vital signs. The readings are continually sent to central monitoring units outside the room instead of being beside the patients, to ensure less contacting between the medical staff and patients, also the cloud is used for those who leave the hospital, as the design can track on their medical cases. Data presentation and analysis were accomplished by the LabVIEW program. A Graphical User Interface (GUI) has been created by the Virtual-Instrument (VI) of this program that offer real-time access to monitor patients’ measurements. If unhealthy states are detected, the design triggers alerts and sends SMS message to the doctor. Furthermore, the clinicians can scan a QR code (which is assigned to each patient individually) to access its real-time measurements. The system also utilizes Electrocardiography (ECG) to detect abnormalities and identify specific heart diseases based on its extracted parameters to encourage patients to seek timely medical attention, while aiding doctors in making well-informed decisions. To evaluate the system’s performance, it is tested in the hospital on many patients of different ages and diseases as well. According to the results, the accuracy measurement of SpO2 was about 98.39%, 97.7% for (heart rate) and 98.7% for body temperature. This shows that the system can offer many patients receiving health services from various facilities, and it ensures efficient data management, access control, real-time monitoring, and secure patient information aligning with healthcare standards.