Traditionally, the Timed Up and Go (TUG) test is used to assess fall risk and functional mobility, and it is often used to track functional changes as neurodegenerative conditions progress. However, TUG frequently relies on visual assessment by clinicians, and results may vary with individual experience. In contrast, aiGait quantifies key components of gait and converts a patient’s walking features and changes across follow-up visits into objective, comparable metrics—helping clinicians more sensitively capture trends over time for clinical assessment, care adjustments, and research analysis.
The core technology essential to this achievement was Fujitsu’s HMA. HMA is a data analysis platform driven by computer vision, based on a high-precision posture recognition AI. This technology, built on the accumulated expertise in developing gymnastics scoring systems, is capable of precisely visualizing complex or high-speed human movements.
The key feature of HMA is that it can analyze motion using video footage captured by standard cameras such as those installed on smart devices, leveraging its advanced recognition capability. As HMA can digitize complicated human motion based on its footage, it accommodates situations where it is difficult to attach markers to the subject’s body. Furthermore, with the use of a highly accurate AI model and a proprietary correction algorithm, precise analysis is achieved, minimizing the inconsistencies in posture recognition that were previously a challenge.
Regarding the reason why Acer Medical focuses on gait analysis using HMA, Allen Lien explains as follows: “Daily gait patterns contain a vast amount of health information. By observing them, we can identify post-stroke prognosis, frailty status, and fall risk. HMA’s appeal lies in its ability to obtain medically valid data solely through gait observation, without requiring special tests like blood tests, to facilitate early detection of diseases. In addition, as this technology does not use markers, its ability to minimize psychological and physical burden on the subjects, and its flexibility for deployment in any location, are significant strengths as well.”
Furthermore, quantifying information and enabling anyone to make the same judgment, regardless of the level of their experience or skill, is another major advantage. Allen Lien adds: “Doctors and nurses determine the location of neurological damage by observing subtle changes in a patient’s gait. However, this requires extensive experience and advanced training, making it difficult for less experienced healthcare providers to make such judgments. By adopting HMA as a core technology, we can now precisely measure changes in movements and generate standardized numerical values. I believe this allows anyone, regardless of the level of their experience, to arrive at an objective judgment.”
