To make healthcare more personalized and precise, medical systems have started adopting wearable health monitoring devices, IoT, big data analysis, and Artificial Intelligence. Such health care systems designed and developed around these technologies are referred to as smart healthcare systems.
Healthcare service providers embrace these advanced technologies mainly to resolve their operational challenges. These challenges include over-stressed healthcare personnel, scheduling and tracking the use of biomedical devices, monitoring of patients and providing timely care to them. Health care systems become more efficient and responsive when these challenges are resolved.
A smart healthcare system performs a range of functions to provide timely and efficient care to patients. Some of these functions include:
Real-time Monitoring of patients physiological parameters(e.g., body temperature, blood pressure, heart rate, oxygen level etc.).
Automatic monitoring and tracking of health care personnel.
Automatic monitoring and tracking of health bio-medical devices.
Monitoring child position in the theme park.
Monitoring patients with specific conditions, such as diabetes or Parkinson’s disease
To assist rehabilitation through constant monitoring of a patient’s progress.
To provide Emergency healthcare.
The general model of a smart healthcare system is shown in the figure. It includes the following four elements:
Wearable Sensors and Central Nodes: Wearable sensor nodes measure physiological conditions. For example, sensors for a pulse, respiratory rate, body temperature, blood pressure, blood oxygen sensors, blood-glucose level, fall detection, and joint angle sensors. The central node receives data from the sensor nodes. It processes this information, then forwards the information to an external location.
Short-range Communications: For sensors to communicate with the central node, a short-range communications method is required. There exist many short-range communication protocols (e.g., Bluetooth, NFC). While selecting a communication protocol for short-range communication the parameter such as effects on the human body, security, and latency are used.
Long Range Communications Data obtained by the central node needs to forward to a central server which may be a cloud-based database server or application server for archival and analysis purpose. There are several considerations when selecting a suitable long-range communications protocol for use in a healthcare system, including security, error-correcting capabilities, robustness against interference, low latency, and high availability.
Cloud Storage and Analytics Medical information obtained from patients is then stored securely on a cloud server. Further, this data is utilised by machine learning algorithms for analysis purpose.
Smart health care systems have to address computational and security challenges. The Fog-based platforms tackle the computational challenges by bringing resources closer to the patients, reducing response time, and providing energy-efficient data processing. Preserving the privacy of the patient's data and making health care services available round the clock are some of the security challenges that need to be addressed effectively. The use of blockchain technology is being explored in recent years to address security and privacy challenges.