Researchers at Tohoku University have developed a new prediction method that employs pressure sensors installed on a conventional office chair. The “smart chairs” sensors detect workers’ movements on the chair dynamically and quantitatively.

The smart chair was tested in a real-life setting outside of the lab. Amassing data from 22 study participants over a period of 3 months, the research group combed through the information to investigate the dynamics of sitting behavior and identify a predictable low back pain progression.

Further aided by various machine learning methods, the researchers discovered a common motif present in the sitting behavior of most participants. They pinpointed small motions in the body trunk that prevent the fixation of vertebral joints, therefore avoiding LBP’s progression. The frequency of this motif could be used to predict the worsening of LBP throughout the day when compared to a morning reference state.

The research group hopes to apply the technology to other areas of the body.

“Although the current method focused on LBP, we hope to collect data relating to head and neck regions to be able to predict and prevent stiff necks and headaches,” coauthor Ryoichi Nagatomi says.

The study was published in the journal Frontiers in Physiology.

[Source(s): Tohoku University, Science Daily]