AI healthcare solutions for remote patient monitoring are quickly becoming recognized as a highly successful method for the treatment of chronic illnesses. RPM is the gathering and distribution of patient health information to service providers outside of the context of conventional care. Without the need for frequent visits and physical tests, this captured data helps monitor patient health.
RPM uses connected devices to record and send the provider's vital data, including blood pressure, heart rate, and oxygen saturation levels. They are outfitted with Artificial Intelligence (AI) to deliver higher-quality care. Thanks to AI technology, remote health monitoring device manufacturers have designed machines exhibiting human-like traits, including reasoning, learning, planning, and creativity.
Clairvoyance Tech is a manufacturer dedicated to using cutting-edge technological solutions to create consumer electronics that can save lives. Their goal is to measure, manage, and monitor critical factors to prevent deadly medical incidents and facilitate quick action if they occur. They are also working on offering clinical-grade remote health monitoring and diagnostic solutions powered by IOT and AI.
Here is the List of AI Healthcare Solutions for RPM
1. Facial Recognition for RPM
A person can be recognized using face recognition technology based on unique facial characteristics, including bone structure and skin texture. Security typically makes use of face recognition. By scanning each person that enters a building, law enforcement may identify and detect individuals.
A list of people with possible criminal histories or those who are prohibited from entering the institution is compared to the scanned face. Face recognition is employed in the healthcare sector in addition to security. Simply scanning a person's face in front of their laptop or smartphone's camera, facial recognition in telemedicine is used to track vital signs.
Face recognition technology, such as that used in RPM, is non-invasive and contact-free, making it possible to diagnose and treat patients without needing repeated doctor trips or hospital stays. This is additionally utilized in mental health therapy to identify emotions.
By analyzing facial landmarks and cues, this technology can be utilized to decipher a patient's inner feelings, giving medical professionals a deeper understanding of their patients. As a result, patients can get tailored, patient-centered, effective care delivered on time.
2. Computer Vision for Remote Consultation
Using digital images, videos, and other visual inputs, CV is a subfield of AI that enables computers and systems to extract useful information from them and act or recommend responding to that information. If AI gives computers the ability to think, CV gives them the ability to observe, watch, and comprehend.
With its powers, CV significantly enhances healthcare, from identifying skin-related disorders like skin cancer to interpreting ECG. Additionally, there have been significant developments in breast cancer screening.
Mammography images can be examined using a CV to detect breast malignancies accurately. Furthermore, lung CT scan pictures analyzed with CV algorithms have shown potential for early lung cancer detection. In RPM, healthcare professionals began utilizing a CV to identify and treat skin conditions without an in-person consultation. CV can reliably and quickly diagnose skin illnesses, enabling medical professionals to treat more patients.
3. Natural Language Processing (NLP) for Remote Diagnosis and Preventive Treatment
NLP technology gives computers the ability to understand human speech or text communications. If CV allows computers to see and comprehend, NLP enables computers to listen. One famous app that uses NLP is a chatbot that asks the same questions as a doctor would during an in-person checkup.
The app does not make an official diagnosis; instead, it uses voice and language processing to extract information such as the signs and symptoms of the patient. The chatbot then sends this extracted information to the doctor, who makes a diagnosis and prepares for treatments based on the received, processed data. With NLP, patients can be monitored remotely. Remote diagnosis and treatment are also possible.
4. RPM Utilizing Sound Analysis
Sound or audio analysis is a broad field of AI that covers automated speech recognition (ASR), digital signal processing, music classification, tagging and production, and other related technologies. Most disorders associated with an obstructed or restricted respiratory system can be identified by breathing sounds. These include COPD and pneumonia. Anomalies of the airway may result in strange breathing noises. The latter type of sound is referred to as adventitious. Auscultation is a technique in which an expert uses a stethoscope to listen for weird sounds and uses this information to diagnose. However, accurately detecting these noises requires both the presence and degree of knowledge of an “expert.” Sound analysis can help detect and monitor disorders such as asthma, chronic obstructive pulmonary disease (COPD), and pneumonia. RPM providers are still exploring this area.
RPM can utilize ECG at-home devices that use a single lead ECG and a deep neural network model trained on various datasets of heart readings. In addition to ECG, sound analysis may be used to examine heart health and the heartbeat. Since it coincides with the cardiac beat, sound analysis can identify the vibration of tissue generated by turbulent blood flow, known as a murmur, which is difficult to detect with the human ear.
5. AI-Enabled Wearables for Connected Health Monitoring
Wearables are healthcare devices that users can wear. These electronic devices are designed to extract data about the users with sensors to monitor their health conditions. The data extracted includes heart rate, respiratory rate, blood pressure, body temperature, and so much more.
Wearables are usually used for monitoring patients remotely. Traditionally, a wearable would collect and transmit data to the provider. The provider views and examines the collected data and warns the patient in case of an abnormal result. However, with AI-enabled wearables, the device will immediately warn the user if they should medical attention, like when the user’s heart is beating too fast or too slow. This allows the user to take the necessary precautions before their condition worsens.
Check Out: 10 Internet Of Things (IoT) Healthcare Examples
6. Predictive Analytics for RPM
Predictive analytics in healthcare is the analysis of current and historical healthcare data that enables healthcare practitioners to identify potential possibilities to improve operational and clinical decision-making, forecast trends, and even manage disease transmission.
With the patients’ data collected through RPM, physicians may effectively manage rising-risk and at-risk groups, prioritize patients with immediate care needs, and reduce avoidable hospitalizations, especially those with chronic diseases.
RPM and AI have the potential to offer proactive care and the ability to anticipate adverse outcomes without the need for frequent visits to the doctor. It can also assist in better allocating limited healthcare resources by focusing on people with more urgent conditions. Practical implementations of RPM and AI healthcare solutions will continue to drive fundamental improvements in the delivery of healthcare services.
Analysts have pointed out that the acquisition is a component of the business's more comprehensive plan to create an omnipresent ambient smart system. Consider what Google might do with roughly 30 million people using fitness trackers. At least one AI healthcare device for remote patient monitoring, with healthcare data, can give a total healthcare check for people.
Latest Post: