Quantitative measurement of gait, or walking patterns, is used in clinical settings as a source of diagnostic and therapeutic information. Subtle and minute aspects of gait, if detected and correctly analysed, can be used to screen for degenerative conditions such as Parkinson’s or Alzheimer’s.
The TRIL Gait Analysis Platform (GAP) is an intelligent diagnostic systems and screening tool for understanding gait patterns in an inexpensive way. It means there’s no need for the immobile and costly technologies that are typically a feature of specialist clinics. The TRIL GAP consists of two body worn kinematic sensors (SHIMMER™) attached to a person’s shins that transmit data about their gait wirelessly to a desktop computer. That information, when analysed with an algorithm developed by TRIL bio-medical engineers, can be used to determine the risk of someone falling.
SHIMMER™ is a lightweight, low-power, body-worn wireless sensor pl
atform which communicates via Bluetooth technology. The SHIMMER™ kinematic sensors quantify movement in three dimensions using an accelerometer and gyroscopes. The TRIL GAP is a portable, low-cost solution for in-home and ambulatory evaluation of gait.
Quantitative assessment of Falls Risk using Timed Up and Go Test (TUG)
Falls are the most common cause of injury and hospitalisation in older adults. They are also the principal causes of death and disability in this age group globally. An estimated 30% of older adults aged 65 and over fall each year leading to enormous direct and indirect societal costs. The cost of falls is estimated to be over $23 billion in the US alone. A system which could provide an accurate assessment of falls risk prior to falling could facilitate timely medical intervention, helping to ease the burden on over stretched healthcare systems. Currently falls risk is assessed using a variety of clinical scales which can be subjective and variable in their administration. There is currently no commercially available method for quantitative assessment of falls risk.
The TUG test is a standard mobility assessment that is associated with risk of falls. The gait and balance of 349 community dwelling elderly adults was assessed using shank mounted tri-axial gyroscopes. Patients were then followed up two years later to determine if they had fallen. This study aimed to determine if a method based on body-worn sensor data from Patients performing the TUG test can reliably predict future falls in community dwelling elderly adults. Results suggest that the method is significantly more accurate at predicting falls when compared to two standard clinical methods (Berg balance scale and time to complete TUG test).
Results suggest that the TUG test combined with body-worn sensors could lead to a simple method that health care professionals could apply to accurately assess future falls risk.