Hello I'm Kecheng. I will introduce ViscoCam,
A Smartphone-based Drink Viscosity Control Assistant for Dysphagia Patients
Swallowing requires the coordination of up to 26 muscles, and the contraction of those
muscles is tailored to fluid property. Any problems in this process may cause dysphagia.
This disease is common in the senior population. 30-40% of people over 65
years old can be affected by dysphagia. Dysphagia can also appear in some prematurely born babies.
Dysphagia patients cannot directly consume liquid like water because water flow too fast, and it may
enter lungs and cause respiratory infections. To reduce risk, diet modification is usually used.
By adding artificial thickener, the liquid can be thickened so it will take more time to travel
through the throat, and patient can achieve timely airway closure or have better muscular control.
The daily life liquid intake should be maintained at certain viscosity level
to ensure safety depending on each patient's condition.
this level is usually suggested by speech and language therapist
So, a method is needed to measure the liquid viscosity in daily life setting
to help dysphagia patients maintain a suitable liquid thickness level.
Let's have a look at existing methods. Viscosity can be measured accurately. The National Dysphagia
Diet standard has classified liquid into 4 levels based on the viscosity ranges.
But measuring viscosity accurately require expensive lab machines,
like viscometer or rheometer. These machines are also difficult to obtain in daily life.
There are some approximate method
Some standards are based on visual observation. For example, liquid is classified by observing
the liquid movement in a spoon. This method is easy to perform, but not accurate.
The healthcare community has proposed some objective methods. Here are 2 examples.
Liquid flow test measure how fast the liquid flow out of a standardized syringe
in 10 seconds. liquid with higher viscosity will have more liquid remained.
Line spread test approximate the viscosity with the distance
fluid has spread over on the horizontal surface in 1 minute.
Because liquid with higher viscosity will spread slower, so the distance is smaller.
These methods are more economical than lab machines.
But there are still some limitations. They still require special apparatus,
and carefully control the timing. They may pollute the liquid because of direct contact.
Can there be a new objective method that is clean suitable for use in daily life?
We present viscocam. It can perform the viscosity measurement with only a smartphone.
just place it on top of the plastic cup containing the liquid to be tested,
then just shake it to start the measurement.
It does not pollute the liquid, have low hardware requirement
and is simple to operate in daily life.
The property related to liquid viscosity that we use is liquids sloshing.
when a person walks while holding a cup of coffee.
When liquid's center of gravity moves, the liquid may move in on direction,
and we can see the increase and decrease of the liquid height on one side.
Sloshing will stop because of liquid internal friction. In this video, the liquid height will
gradually decrease. The rate of decrease can be associated with liquid viscosity.
Thicker liquid takes less time to stabilize than thin liquid. By sensing the sloshing
wave amplitude and obtain its weakening speed, we can infer the liquid viscosity.
So how can we measure the liquid wave height inside a cup in real time?
We use light refraction.
Imaging looking at a swimming pool, you may see the view of the swimming pool bottom
is distorted. This is because the light from the bottom is
refracted on the surface of the liquid and the position is shifted.
From physics, we know the degree of this shift is related to the wave height.
The distortion of refraction image sequence
Is related to the propagation of the liquid's free surface waves.
By observing such distortion, we can deduce the motion on the liquid free surface.
To sense the liquid surface wave height changes,
we use optical flow. it is a measurement of the pixel displacement among consecutive frames.
So if a smartphone camera is pointed downwards through the liquid,
and when the liquid is sloshing, the distortion of the view will indicate the direction and magnitude
of the liquid sloshing. The corresponding optical flow can represent such information.
Here is the overview of the system.
Video frames and optical flows frames are used to trained a 3D Convolutional Neural Network .
During inference, the video is trimmed so that the process of sensing the liquid sloshing
decay will not be affected by external forces.
Then it pass the Neural Network for feature extraction
and classification. The output is the liquid viscosity level.
To evaluate the performance, we followed the IDDSI standard by classify 3 liquid types:
thin, slightly thick, mildly thick. we achieved 96% accuracy.
We show that the system is robust to a range of testing conditions
like different cup sizes, liquid depths, liquid color and different users.
ViscoCam is a drink viscosity control assistant for dysphagia
patients that only require a smartphone it is clean, convenient to use in daily life.