Hello from Germany!
My name is Florian Wolling, I am research associate and PhD candidate
of the Ubiquitous Computing lab at the University of Siegen.
Today, I am presenting
“IBSync: Intra-body Synchronization of Wearable Devices Using Artificial ECG Landmarks”.
The synchronization of distributed wearable devices is a persistent challenge
and particularly machine learning approaches suffer from unmatched time.
Both wireless online and motion-based offline synchronization techniques
address this problem but tend to be either energy-intensive or cumbersome and obtrusive.
In contrast, we propose IBSync which enables the implicit and incidental synchronization.
The exemplary scenario shows a person sitting at a desk, wearing two devices at the wrists.
A large electrode is placed under the front edge of the desktop
and serves as a transmitter of landmark signals.
Intra-body communication is a promising yet underinvestigated principle which
can be seen as intermediate between wired and wireless communication, with advantages over both.
Capacitively induced into the human body, the landmarks are detected
by the wearables’ repurposed analog ECG front-ends.
Therefore, the wearer catches the landmarks by simply touching, approaching,
or passing certain areas or surfaces.
The environmental ground is required to close the circuit
and hence to form the weak transmission channel.
The transmitter’s setup is fairly simple.
A conventional microcontroller is connected to and supplied by a stationary computer,
and hence connected to common ground.
Every 2.5 s, the computer requests the transmission of a landmark.
Thereupon, the microcontroller simply toggles a general purpose IO
and hence charges or discharges the electrode.
To receive the landmarks, the analog ECG front-ends of
commercially available reference designs are repurposed.
The devices allow not only access to the raw measurements
but even to directly configure the sensor and to run a custom program.
The devices’ positive input at the front and the negative input at the back
form the capacitive coupling electrode sandwich for intra-body communication.
A third contact at the back establishes a driven-right-leg circuit
to improve the amplifier’s common-mode noise rejection.
The transmitter‘s landmark packets are composed of pulses, modulated at tuned 20 Hz.
The packet frame mainly consists of 8 pulses preamble and 4 pulses terminator.
In this way, the frame enables the general detection of landmarks in the devices’ measurements.
Furthermore, two delimiter symbols embrace 8 pulses or gaps which represent
8 bit of data in an on-off keying modulation scheme.
This additional information allows for either the unique assignment of
coincident landmarks across devices, or even their allocation
in the transmitter’s absolute time.
Due to the inherent high-pass transmission characteristics of the human body,
the detected signal is not showing a rectangular wave anymore.
Instead, the signal resembles to its first derivative and stems from the charging
and discharging current peaks respectively.
Still, those enable the precise alignment of coincident landmarks
that are instantaneously available throughout the entire body surface.
To determine the most suitable frequency band, we first recorded
the noise floor from an everyday life setting.
Accordingly, the most suitable frequency band ranges from 10 to 48 Hz.
While the body channel favors a higher carrier frequency,
the sampling rate of 128 Hz, and hence a Nyquist frequency of 64 Hz, demand for a lower one
to increase the sample coverage per unit pulse.
As a trade-off, we decided for a modulation frequency of 20 Hz.
Diverse filters are applied to suppress noise and to extract the desired signal.
A wider passband is required to cover the harmonics in the sidebands,
which allow for a faster transient response.
The synchronization process starts with the Short-time Fourier Transform.
It is applied to the preprocessed measurements, to extract
the frequency components associated with the artificial landmark signal.
Then the intervals of interest are identified based on the derived Signal-to-noise Ratio.
Within these intervals, Pearson‘s normalized cross-correlation
allows to search for the landmarks.
Derived from the frame, a general template allows to locate all potential landmark positions.
A template derived from a specific landmark packet, including the
unique data, then allows to assign specific landmarks across different devices.
Finally, the contained information even allows to allocate those
in the transmitter’s absolute time.
To evaluate the proposed method, we performed three experiments in the exemplary
desktop scenario: directly touching the electrode, touching the desktop, and leaning back
with the hands off and probably coupling through the thighs.
All in all, we achieved very good alignment accuracies with
minor average errors but a comparably substantial standard deviation.
We have presented IBSync, a novel method for the synchronization of wearable sensing devices.
Further, we propose to repurpose the analog ECG front-ends of modern wearables
to capture artificial landmark signals.
The wearer can catch these by simply touching, approaching, or passing certain areas or surfaces.
We achieved an accuracy in the order of about 4 samples, 33 ms respectively.
The results are promising, there is, however, still more room for improvement
in the correlation precision.
Also, the system is not entirely wearable yet but uses a stationary transmitter.
Improvements of the electrode and modulation would likely solve this issue.
Thank you for your interest in this topic.
I am looking forward to answering your questions!