AI Gaits Analysis

Development & Training of an AI Application to

Detect Unsteady Gaits

In a collaboration between Singapore General Hospital (SGH), and Nanyang Polytechnic’s (NYP) School of Engineering, an innovative gait analysis system using Artificial Intelligence (AI) has been developed for the hospital’s emergency department.

The innovation...

The innovative solution utilizes the existing CCTV cameras in the hospital to monitor incoming patients and detect unsteady gaits, enabling hospital staff to promptly identify and prioritize those in need of immediate assistance. This not only enhances patient care but also optimizes the allocation of resources in a fast-paced emergency environment.

The development of this system posed several challenges, which the School of Engineering, spearheaded by Dr. Kong Wai Ming took on. Combining their expertise, the team designed a project that required high accuracy and intensive computation for the deep learning AI algorithm, along with the use of the Dynamic Time Warping (DTW) algorithm. The team also overcame some hurdles, such as suboptimal viewing angles from the existing CCTV cameras and the need to detect multiple individuals from both front and back angles using a single camera.

A sense of accomplishment...

One critical requirement of this project was real-time feedback, to alert clinical staff when patients with unsteady gaits are identified, thereby preventing falls, and related injuries. Through rigorous program evaluation, the team achieved this essential feature, enhancing safety and ensuring that patients receive the immediate attention they require.

This collaboration has paved the way for further development of the gait analysis system. SGH and NYP are actively exploring avenues to refine the technology, with the potential for its application in other medical institutions such as nursing homes, rehabilitation centres, and more.

This collaboration also demonstrates Nanyang Polytechnic's capabilities in advanced AI gait analysis and reinforces its commitment to innovation in healthcare.

A message from Singapore General Hospital...

Falls within hospitals are a major safety issue. 30-50% of falls result in injuries, contributing to an average increased hospitalization length of stay of 6.3 days and $14,000 additional medical costs per admission. In the elderly, falls often result in decreased mobility and loss of independence, thus burdening healthcare systems. Crowds, blind corners, and long corridors in the hospital make it difficult to have direct line of sight to all patients. As such, we wanted to explore using existing CCTV to keep an additional ‘eye’ on patients who may be unsteady and at risk of falling.

We learnt a lot during this collaboration. Although this was a pilot study in a controlled setting with pre-recorded CCTV footage, we believe that this project has potential and hope to carry on work to further improve accuracy and integrate it such that it can analyse real-time CCTV footage. If successful, we believe it can be used in many different hospital, emergency department, and outpatient clinic settings, and hence greatly enhance patient safety.

The Industry Project Chronicles Team

November 2023

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