Thread-Based Sensors Measure Head Movements in Real Time

Tufts University engineers have designed and demonstrated new flexible thread-based sensors that are capable of measuring the neck movements, offering information on the direction, degree of displacement and angle of rotation of the head.

This latest finding offers the possibility for thin and unobtrusive patches that are similar to tattoos and could, according to the team from Tufts University, track drivers’ or workers’ fatigue, quantify athletic performance, help with physical therapy, enhance computer-generated imagery in cinematography and improve virtual reality systems and games.

Recently described in the Scientific Reports journal, the new technology adds to an increasing number of thread-based sensors designed by engineers from Tufts University. These sensors can be woven into textiles, quantifying metabolites in sweat, or chemicals and gases in the environment.

During the experiments, a couple of threads were placed in an 'X' pattern on the rear side of a subject’s neck. When the threads bend, the sensors coated with an electrically conducting carbon-based ink detect the movements, producing strain that modifies the way these sensors conduct electricity.

When a series of head movements are performed by the subject, the wires transmit signals to a tiny Bluetooth module, which subsequently transmits the data wirelessly to a smartphone or PC for further analysis.

Advanced machine learning approaches were used in the data analysis to understand the signals and decode them to quantitate the movements of the head in real time and with an accuracy of 93%.

In this manner, the processor and sensors monitor the movement without any kind of interference from large devices, wires, or restricting conditions, like the use of cameras, or confinement to a laboratory or room space.

Algorithms will have to be specialized for every site on the body, but according to the research team, the proof of principle shows that thread-based sensors can potentially be used for measuring movements in other limbs.

Scientists could use the skin patches or even form-fitting clothing comprising the threads to monitor the movements in surroundings, where the measurements are highly applicable, for example, in a classroom, the workplace, or in the field. Moreover, the fact that a camera is not required offers more privacy.

This is a promising demonstration of how we could make sensors that monitor our health, performance, and environment in a non-intrusive way. More work needs to be done to improve the sensors’ scope and precision, which in this case could mean gathering data from a larger array of threads regularly spaced or arranged in a pattern, and developing algorithms that improve the quantification of articulated movement.

Yiwen Jiang, Study First Author and Undergraduate Student, School of Engineering, Tufts University

There are other kinds of wearable motion sensor designs that comprise three-axis gyroscopes, magnetometers, and accelerometers to sense the movement of subjects with respect to their environments.

Such sensors are built on inertial measurements—measuring how the body moves up and down, rotates, or expedites—and tend to be more difficult and bulkier.

For instance, if other systems are used to quantify the movement of the head, one sensor needs to be placed on the forehead, while another one should be positioned in the neck above the vertebrae. This conspicuous placement of sensors can interfere with the free movements of subjects or simply the ease of not being conscious of being quantified.

For situations, like on the athletic field, the paradigm of the new thread-based sensor could well be a game-changer.

When thin tatoo-like patches are placed on various joints, athletes would be able to carry motion sensors to sense their form and physical movements, whereas thread-based sweat sensors, illustrated in a previous study by the Tufts University researchers, could also monitor their lactate, electrolytes and other biological markers of performance in sweat.

In conclusion, a thread sensor patch may alert the fatigue of truck drivers, or other scenarios where it is crucial to track operator alertness, or monitor the head movements of individuals who are about to nod off.

If we can take this technology further, there could be a wide range of applications in healthcare as well. For example, those researching Parkinson’s disease and other neuromuscular diseases could also track movements of subjects in their normal settings and daily lives to gather data on their condition and the effectiveness of treatments.

Yiwen Jiang, Study First Author and Undergraduate Student, School of Engineering, Tufts University

“The objective in creating thread-based sensors is to make them ‘disappear’ as far as the person wearing them is concerned,” stated Sameer Sonkusale, a professor of electrical and computer engineering at the School of Engineering of Tufts University and director of the Tufts Nanolab, and the corresponding author of the study.

Creating a coated thread capable of measuring movement is a remarkable achievement, made even more notable by the fact that Yiwen developed this invention as an undergraduate. We look forward to refining the technology and exploring its many possibilities.

Sameer Sonkusale, Professor of Electrical and Computer Engineering, School of Engineering, Tufts University

Journal Reference:

Jiang, Y., et al. (2021) Head motion classification using thread-based sensor and machine learning algorithm. Scientific Reports. doi.org/10.1038/s41598-021-81284-7.

Source: https://now.tufts.edu/