Telemedicine and Medical Artificial Intelligence
Telemedicine is the technology of remote monitoring, diagnosis, and sometimes treatment, without having to be co-located with the patient. The deployment of medical artificial intelligence is now necessary to digitize cases, and then, “We need to change from the past information collection (electronic cases) to more active remote testing, detection, and defense functions, which Freescale calls “Wellness”. Lisa T. Su The Ph.D. prospected embedded control for its contribution to medical electronics.
At present, telemedicine usually uses some portable or home diagnostic devices to measure blood pressure, heart rate and other vital signs for tracking. Then, you must upload these results to your PC and send them to the doctor or medical provider via the network to monitor the results. In this process, many people intervened.
Advances in network technology continue to improve on this. For example, nurses at St. John’s Hospital in New Brunswick, Canada, measure the vital signs of patients who rest at home after surgery to determine whether they are recovering properly or need other assistance. This In fact, has reduced the medical cost of patients, and vacated the post-surgical beds that are very scarce in hospitals, and made patients more comfortable at home.”
Although today’s telemedicine has made great progress, there are still many things to do. The next step is to make intelligent devices and systems without diagnosis, and truly achieve advanced treatment through automatic telemedicine.
In automated telemedicine, key drug therapies can be adjusted in real time based on information collected by networked sensors and devices. By comparing the patient’s real-time data and historical data, the dose can be adjusted automatically within a reasonable range.
Embedded intelligence not only plays a role in the above fields, but also enables robotic surgery through telemedicine. At present, by using a joystick that can eliminate the normal shaking of human hands, doctors can perform local robotic surgery, thereby helping surgeons perform more precise surgery.
Robotic surgery is currently only used when patients and doctors are in the same ward. In the future, problems such as network delays and video will be solved. At that time, we are expected to perform remote robot surgery, because medical experts can basically be distributed on demand around the world.
The conditions needed to achieve this goal are partially in place. High-quality network with near-perfect delays must be guaranteed to send video images and control the robot. We NOW have fast, powerful multi-core processing and advanced networking capabilities, improved network bandwidth and video compression.
The supercomputer can defeat chess champion Gary Kasparov because it stores a lot of past games, strategies and results. Medical artificial intelligence uses advanced algorithms based on years of actual medical data and medical records to help doctors make better decisions.
Medical artificial intelligence is not really a new concept. About 10 years ago, researchers developed a system using artificial intelligence to diagnose the risk of heart attack, which is 10% more efficient than most senior cardiologists. However, with embedded intelligence, its ability to manage and process large amounts of data and richer data types will make these systems more advanced in terms of diagnostic capabilities.
In the next 5 years, we envision that medical artificial intelligence systems can not only use complex algorithms for intelligent decision-making, but also truly learn by capturing, analyzing, and adjusting continuous real-time patient data streams.
For example, researchers are experimenting with the use of medical artificial intelligence and sensor networks to help Alzheimer’s patients live a happier, healthier and safer life. Some common symptoms of Alzheimer’s patients are forgetfulness and confusion, which sometimes puts them in great danger. To solve this problem, researchers are developing a system that can automatically collect patient data from sensor networks in the home and analyze the data using medical artificial intelligence.
Supporting all this is to transform the patient’s family into a “smart home”: sensors will be integrated with everyday objects to determine whether the patient opens the stove, or whether to open the refrigerator, cabinet or gate, etc.; the heat and pressure sensors will determine whether the patient is sitting on a chair, laying on a bed, or walking around the house; biosensors will measure vital signs such as heart rate and body temperature, and tell us about their condition.
The real-time data from these sensors together provide a very clear picture of the patient’s position and mental state indoors. If the artificial intelligence system detects an abnormal situation, it will automatically trigger an emergency response to remind the patient to eat or take medicine, or if there is no activity recorded in the room within a certain period of time, it will automatically call the emergency number.
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