Telemedicine monitoring mainly uses technologies related to the Internet of Things (IoT) technology to build a patient-centric, remote consultation and continuous monitoring service system focused on helping critically ill patients. The original purpose of designing telemedicine monitoring technology was to reduce the number of patients entering hospitals and clinics.
According to the Centers for Disease Control and Prevention (CDC), about 50% of Americans have at least one chronic disease, and their treatment costs account for more than three-quarters of the nation's USD 2 trillion in medical expenditures. In addition to the high cost of high-tech treatment and surgery, doctors spend roughly billions of dollars on routine checks, laboratory tests, and other monitoring services.
With the advancement of telemedicine technology, sophisticated sensors can be used to monitor patients with real-time updates. Furthermore, the focus of telemedicine monitoring has gradually shifted from improving lifestyles to quickly providing lifesaving information and to medical programs focused on educational exchange.
In practical applications, health information of residents can be transmitted through the internet, improving the quality of medical services. This technology also allows doctors to conduct virtual consultations and provide intellectual support to other hospitals by experts from a large hospital. This will extend high-quality medical resources to primary health care institutions, help establish a long-term continuous education service system for clinical cases, and enhance the quality of continuing education for primary health care workers.
Computer scientists at the University of Adelaide are leading a project to develop new RFID sensor systems that support older people safely stay independent. Researchers used RFID and sensor technology to identify and monitor people's activities automatically. This can help with both routine care and emergency care in the case of an accident within the home. Additionally, the system features low input costs and no requirements for intensive testing. In the face of an aging population, this application has enormous potential.
The task of a smart wheelchair is to safely and comfortably deliver the user to a destination. During use, the wheelchair not only needs to accept the user's instruction but also needs to start its obstacle avoidance, navigation, and other functional modules in response to environmental information. Unlike a self-driven mobile robot, the wheelchair and the user are a collaborative system. Numerous factors such as design, safety, comfort, and ease of operation are (or at least should be) the most critical factors in smart wheelchair design.
Differences in potential users' physical capabilities means that smart wheelchair design must also be flexible and modular. Each user should be able to choose the correct modules by their type and degree of disability. Functional modules should be both removable and replaceable, so that wheelchair function is modifiable as health levels change.
The general function of the smart wheelchair gets divided into the following sub-functions: environmental perception and navigation functions, control functions, driving functions and human-computer interaction. Through the functional analysis and modularization of the smart wheelchair’s features coupled with specific research results, the system will likely consist of three main parts: the Sensor Module, the Drive Control Module, and the Human Interface Module.
The sensor module would consist of two parts - internal state perception and external environment perception. The attitude sensor determines the attitude and positional information of the wheelchair. The displacement speed and distance of the encoder provides the self-positioning information. Visual, ultrasonic and proximity switches are mainly responsible for continuously obtaining information about obstacles. For the drive control module, rear wheel configuration of a motor would get used with ordinary electric wheelchair control operations - front, back, left and right. Human-computer interaction is either done with physical controls such as a joystick or mouth stick or software controls such as a personal computer.
A smart wheelchair has two independent drive wheels, each equipped with a motor controller. The real-time detection data of the two motor controllers form the odometer relative positioning sensor. The installation of inclination sensor and the gyroscope is done to measure the posture state of the wheelchair during the traveling process.
Ultrasonic sensors and proximity switches obtain ambient information. To achieve a wider range of obstacle information, eight infrared sensors and eight ultrasonic sensors get equipped with the system. Also, installation of a CCD camera is done to determine depth information in front of the chair.
Additionally, the smart wheelchair can balance solely on two wheels. This distinctive feature requires that the wheelchair gets built with a unique structure based on the idea of driving each wheel by a separate DC motor and keeping the balance of the chair’s weight directly above the wheels on a single axis.
This gets achieved by utilizing sensors to determine the pitch and yaw and thus determine the attitude of the chair in real time. Signals from the sensors move to the chair’s processor which runs the information through a control algorithm to determine the optimal speed and direction for each wheel to maintain balance while moving forward or backward.
The smart wheelchair uses a combination of a tilt sensor and a gyroscope to form an attitude sensor capable of determining the wheelchair’s attitude as it travels across a plane. The use of tilt sensor is to determine the wheelchair’s degree of deviation from vertical, whereas the gyroscope determines its angular velocity.
By measuring vital signs such as body temperature and heart rate and forming a personal medical profile for each patient including bodyweight, cholesterol level, body fat, and protein content, we can analyze the patient’s general physical condition and return physiological indicator data to the patient’s community, caretaker, or related medical organization. This allows the patient to make timely revisions to their diet, facilitates the generation of timely personalized medical advice, and provides research data for hospitals and research institutions.
It won’t be long before each person’s cell phone will be like a private doctor.
While everyone certainly has their own experience with these matters, it’s not uncommon in China to see long lines of patients and their mounting frustrations which are visible—waiting to take a registration number and see a doctor. Patients can be overwhelmed by the visit as hospitals are flooded with thousands or tens of thousands of outpatients in a single day.
So how does this system work? When a person becomes ill, he or she wants to see an expert. Hence, how can we efficiently service everyone? Precisely, by encouraging these kinds of changes as we enter the future. Experience makes an expert, and this experience is accumulated by observing data indicators related to the patient’s illness.
If an expert’s experience can be compiled into a database, then, all the patient needs to do is to enter his or her data indicators into the system. When the parameters in the database have reached a sufficient level, the database will be able to perform automatic diagnosis. In the end, the database becomes a kind of "robot expert."
These databases work by collecting an adequate amount of the expert’s cancer cases, combining them to form data indicators, and thus generating a database model. For example, if we have the data indicators from the treatment of 10,000 cases of leukemia, then the database contains 10,000 solutions for treating leukemia.
This kind of databases will eventually transform into a built-in software in our cell phones, increasing the mobility of treatments. If the software is unable to assess the situation efficiently, then a human expert will be able to administer treatment over the internet. In time, each of us will have his or her own "private robot doctor: residing in our phones.
Each person needs to build their health database. If a sufferer of heart disease has created their digital health file, then as soon as their heart begins to behave abnormally or poses an immediate risk, the relevant data will be immediately passed to the system that can use GPS positioning to call the necessary emergency services from the nearest hospital.
This may be a simple IoT application, but in the future, we may all have our own check-up devices at home. All we need to do is, place our palm on the device which will then collect blood pressure, heart rate, pulse, and body temperature. In the future, it might even be able to perform chemical tests.
This data will be then automatically passed to the hospital’s data center, and, if necessary, a doctor will ask us to come into the hospital for further evaluation or go to a nearby treatment center to receive treatment.
When we get on to the metro, just about everything can get accomplished with the swipe of a card. This makes the entire experience much more convenient for the majority of users.
In medical IoT field, seeing a doctor should be similar to getting on the metro.
Over the course of medical treatment, the user’s official ID card is the only legal proof of identity and must get scanned on a card reader, the patient then submitting a certain amount of money as a down payment. In a few seconds, the automated card reader/writer can then produce an "RFID Visit Card" (this could also double as an insurance card) which the patient can use to get a registration number for seeing the doctor.
Once the patient has a card, they can go to see a doctor at any treatment center. At the treatment center, the system will automatically enter their information into the corresponding doctor’s workstation. Throughout treatment, information related to the doctor issuing examinations, medicine, and other treatment information gets passed on to the appropriate departments.
As long as the patient has their "RFID Visit Card," the card reader/writer at the corresponding department can check all of this information, issue medicine, and administer treatment without requiring the patient to run back and forth calculating and making payments. Once the procedure is complete, the fee printer prints out a receipt and cost list.
Also related to "RFID Visit Cards, hospitals shall be able to give in patients an "RFID wristband" which will include the patient’s name, gender, age, profession, check-in time, diagnosis time, examination time, and fee information. The accomplishment of obtaining the patient’s identity information gets done without any manual entry and encryption of patient’s profiles is needed to protect their privacy.
This ensures that the wristband is the only source of the patient’s identification information and avoids human error derived from manual entry. Furthermore, these wristbands will also include positioning functionality, making it impossible for the wearer to sneak out of the hospital.
If a patient forcibly removes their "RFID wristband" or leaves a certain range around the hospital, then the system will issue an alert, triggering an evaluation of the wearer’s vital signs (breathing, heart rate, pulse) and determine the patient’s "threat level" based on that information. The system will be able to evaluate physiological changes 24 hours a day, and when the wearer’s threat level reaches a certain threshold, an alert will be issued automatically to allow hospital staff to respond appropriately as soon as possible.
Examination, imaging, surgery, drug administration, and other tasks common to the treatment process is all facilitated by confirming patient information through their "RFID wristband" and recording the time that each step in the process begins. This ensures that nurses and hospital examination staff at every level administer the appropriate care without error, thus providing the quality of the entire treatment process.
The patient can use their "RFID wristband" to check their treatment fees and specific card reading machines. They can also print their fee results, insurance plans, rules and regulations, nursing instructions, treatment plan, and drug information. This will serve to increase the patient’s ability to obtain their treatment information and increase overall patient satisfaction easily.
The application of IoT is increasing day by day in every aspect of the healthcare industry. In this article, we have explored various applications of IoT in different verticals of the medical industry. Starting from the drug monitoring and management, digitization of hospitals to telemedicine care, we talked about every possible area in which IoT technology can enhance the processes.
To know more about IoT solutions, visit www.alibabacloud.com.
Applications of the Internet of Things in the Medical Industry (1) – Digital Hospitals
2,599 posts | 764 followers
FollowAsiaStar Focus - June 30, 2022
Amuthan Nallathambi - May 12, 2024
Alibaba Clouder - June 14, 2018
AsiaStar Focus - July 1, 2022
Alibaba Clouder - March 2, 2017
Alibaba Clouder - January 19, 2021
2,599 posts | 764 followers
Follow
E-MapReduce Service
A Big Data service that uses Apache Hadoop and Spark to process and analyze data
Learn More
MaxCompute
Conduct large-scale data warehousing with MaxCompute
Learn More
DataWorks
A secure environment for offline data development, with powerful Open APIs, to create an ecosystem for redevelopment.
Learn MoreMore Posts by Alibaba Clouder
