Leveraging AI for Better Patient Monitoring

Healthcare facilities throughout the world are suffering from critical staff shortages, and the COVID-19 pandemic has only made the situation worse. According to November 2020 statistics from the U.S. Department of Health and Human Services, 18% of U.S. hospitals said that they were critically short on medical staff. Patient monitoring AI can dramatically improve the ability of hospitals and medical facilities to monitor situations.

Staffing shortages have made it difficult for hospitals to provide sufficient monitoring of patients who require immediate attention. Tragically, a wide range of patient behaviors – like sitting up, getting out of bed, coughing, falling, or gesturing for help – go unnoticed until it’s too late to help the patient in need. Patient monitoring AI can be life saving in these situations.

Patient Monitoring with Computer Vision

The Tragic Cost of Patient Monitoring Failures

Diligent visual monitoring of patients is key to ensuring the best medical outcomes, but even a fully staffed hospital or medical facility can’t keep an eye on everything. Here are some examples of the tragic cost of patient monitoring failures:


Medical patients in hospitals, nursing homes, and other health facilities are more prone to fall injuries. For example, PSNet reports that medical patients fall approximately 3 to 5 times per 1,000 bed-days. The Agency for Healthcare Research and Quality reports that an estimated 700,000 to 1 million hospital patients fall every year. Moreover, approximately 50% of the 1.6 million U.S. nursing home residents fall every year.

Sadly, over 33% of hospital patient falls result in an injury – and many of these injuries are serious, involving fractures and head trauma. Beyond the injuries, hospital patient falls may be classified as “never events,” which means that the Centers for Medical and Medicaid Services will not reimburse hospitals for the additional medical costs related to the falls, representing a significant financial burden on the hospital.

Considering the risk of fall injuries at medical facilities, medical staff need to know whenever an at-risk patient gets out of bed or suffers a fall. However, it’s impossible to constantly monitor all patients at all times. Considering that medical facilities are usually short on staff, it’s not uncommon for a fallen patient to be left unattended, which can lead to devastating health consequences.

Coughing, Hand Gestures, and Spasms

Patients suffering from coughing fits – or various types of hand gestures and bodily spasms – could be in dire need of assistance to ensure that they are breathing properly and not experiencing a health emergency. Any delay in detecting a patient in this kind of situation could result in a worsened health condition or death.

In many cases, health facilities can be held liable for their patient monitoring failures – especially if those failures are the result of negligence and result in serious injuries or death. Aside from the tragic health consequences and negative impact on patient families, monitoring failures damage the reputations of medical facilities, increase liabilities, and elevate insurance costs.

Leveraging Visual AI for Better Patient Monitoring

Patient monitoring AI technologies can dramatically improve the ability of hospitals and medical facilities to detect instances of patients falling, in addition to monitoring patient behaviors and gestures. A trained computer vision system for patient monitoring can easily detect the following patient gestures, movements, and behaviors:

  • A hospital patient, ICU patient, post-op patient, or visitor who falls down.
  • A patient who swings his or her legs over the side of a bed in preparation to get up.
  • A patient who suddenly sits up in bed.
  • A patient who is suffering from a coughing fit, sneezing fit, or body spasms.
  • A patient who is gesturing his or her arms for help.
  • A patient with a bloody nose after reacting badly to a drug protocol.

At Chooch AI, we can train sophisticated computer vision models to detect all of the above and more. Deployable through the cloud – or on edge devices for maximum security and privacy – these devices can use an existing IoT camera network to gather and interpret visual data on patient and hospital visitor activities. Chooch can also install a visual AI system for patient monitoring on a rollable cart that includes (1) a monitoring camera on the top and (2) a visual AI edge server on the bottom.

Medical staff can position these carts in rooms to monitor patient behavior and provide immediate updates and alerts as required. Any hospital or medical facility can develop and deploy visual AI strategies like these, and start achieving better patient outcomes in a matter of days.

In summary, Chooch AI computer vision models for patient monitoring AI can help hospitals and medical facilities:

  • Monitor patient conditions with greater accuracy and attention to detail.
  • Instantly respond to patient emergencies as soon as a problem arises.
  • More immediately help patients who are experiencing adverse reactions to drugs.
  • Receive instant alerts when a patient or anyone in the hospital falls.
  • Detect unusual patient behaviors such as a patient getting ready to exit his or her bed, coughing, sneezing, or gesturing for help.
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