Sensing finger movements via impedance measurements

Smart clothes, wearables and biosensors do not sound as futuristic as they used to. The development in this field of science and engineering is rapid and it is no longer a niche – as seen in the first or even second generation of such products hitting the market. Although there is wide choice of products, one common aspect is the ability to measure and process signals from the body. Among the signals that can be used, impedance measurements offer non-invasive, yet sensitive detection. These signals, oftentimes very weak, need to be recorded in an accurate, precise and reliable way. This blogpost will demonstrate how the MFIA Impedance Analyzer (or MFLI lock-in amplifier with MF-IA option) can do exactly this, and how the LabOne user interface makes setting up and taking measurements straightforward and quick. Your imagination and creativity know no limits – and neither do ours, so read on to find out how to use MFIA to capture a Boolean logic response using finger tapping as inputs.

Experimental setup 

Taking impedance measurements from the body is not trivial and please note: the MFIA is for laboratory research use only and is not for diagnostic procedures. Much of the success of the measurement depends on the proper placement of electrodes. Here we used 4 ECG electrodes (Ambu BlueSensor Q-00-A) that were placed in line, one next to another on the inside of the left forearm, starting from the wrist towards the elbow of the subject as shown in Figure 1 below. We used a 4 terminal configuration in order to reduce skin-electrode impedance, therefore 4 BNC cables (1m, Amphenol Digikey part no: ACX-2386-ND) with BNC-banana converters (Pomona 1894 Digikey part no: 501-1323-ND) were connected to the on-skin electrodes and each of the 3 signal inputs and 1 signal output of MFIA.

Figure 1: Placement of electrodes on the forearm while performing the taps. Please note that MFIA is for laboratory research use only and is not for diagnostic procedures.

 

Measurement preparation

In order to find the optimal frequency at which the finger movement can be recorded, we  first performed a frequency sweep between 1 kHz and 1 MHz, the signal amplitude was set to 100 mV and the sweep was repeated a few times. The results can be seen in the Figure 2 (click the image to enlarge). The top plot presents the absolute impedance (Z) and the bottom plot the phase of the measured signal. Thanks to the dual plot functionality of LabOne, it is very easy to follow multiple parameters and group them on their own respective axes. Each plot comes with their own set of cursors, that makes the analysis very straightforward. The maximum difference for the Z is 16.3 Ohm, whereas the change in phase is only 9.89 deg, as indicated by the delta value cursors. We chose the frequency 10 kHz for the further measurements as it was at the end of the first plateau – it is indicated by the vertical cursor going through both plots.

Figure 2: Impedance and phase during the initial frequency sweep, range 1 kHz – 1 MHz. Please note that MFIA is for laboratory research use only and is not for diagnostic procedures. (Click the image to enlarge)

 

Individual finger movements

In one of our previous blogs, Bioimpedance of a Muscle Contraction with the MFIA, we were exploring the capabilities of the MFIA to measure the response of the muscles during a fist clench and release. The MFIA was able to track these changes fast and accurately, therefore we decided to take a step further and focus on the movements of individual fingers.

The experiment consisted of a series of taps performed by a single finger, while the relaxed forearm was placed on the table. For the sake of precision it was important to keep the whole arm relaxed (including the shoulder) as we noticed that any muscle tension was easily reflected in the baseline of the impedance signal. During the measurement each finger performs 3 taps of moderate speed and force. The palm and the whole arm should come back to the fully relaxed position before the next tap – which can be monitored in the baseline trace in Figure 3. As in Figure 2, the absolute impedance and phase are being monitored.

Figure 3: Monitoring impedance and phase during 3 consecutive fast taps of the index finger. Baseline for impedance is kept at 61.476 Ohm. Please note that MFIA is for laboratory research use only and is not for diagnostic procedures. (Click the image to enlarge)

In Figure 3 we can see signals acquired via the DAQ module during a fast index finger tap repeated 3 times. A straight baseline (61.476 Ohm), highlighted with the Y1 cursor, indicates that the hand was in a relaxed state between the movements. This corresponds very well with the value of 61.94 Ohm measured for 10 kHz during the frequency sweep (the arm was also kept relaxed). Using the DAQ module allows for saving the data in hdf5 format which can be then easily reloaded and analysed (other data formats are also supported: .csv, .mat, .zview). Data analysis was performed using the Math tools available in LabOne. We observed that phase measurements are more sensitive and allow to clearly evaluate the duration of the finger movement through the use of vertical cursors X1 and X2.

Similar tapping experiments were performed with other fingers and the full impedance data was recorded by the MFIA. An example with 5 middle finger taps is presented in Figure 4. A stable baseline is observed for phase and impedance, -4.449 deg and 62.167 ± 0.022 Ohm, respectively.

Figure 4: Monitoring impedance and phase during 5 consecutive fast taps of the middle finger. Baseline for phase is kept at – 4.449 deg. Please note that MFIA is for laboratory research use only and is not for diagnostic procedures. (Click the image to enlarge)

 

Basic coding with finger tapping

The experiment was repeated for each finger – except the thumb – and the impedance and phase were recorded. In Figure 5 below we can see the results and we see that each finger movement has a unique signature (the signs of both: the phase and the absolute impedance change). For example: index finger (A) exhibits negative Z change and positive phase change, whereas pinky/little finger (B) shows positive Z and phase changes.

Figure 5: A panel of data recorded for each finger (performing 3 taps) A – index finger, B – pinky, C – middle finger, D – ring finger. Impedance traces are in blue, phase traces are green. Please note that MFIA is for laboratory research use only and is not for diagnostic procedures. (Click the image to enlarge)

Taking into consideration the unique signature for each finger it is possible to build a table for fundamental logic functions based on the inputs given by particular fingers – which may be of great interest for developers of smart clothing, sensors and wearables. An example of a simple coding with finger movements is presented in Figure 6 below.

Figure 6: Impedance and phase signals generated by finger tapping – each signal can be attributed to a particular finger (A – index finger, B – pinky, C – middle finger, D – ring finger). Please note that MFIA is for laboratory research use only and is not for diagnostic procedures. (Click the image to enlarge)

 

Thanks to the sensitivity of the MFIA and the ease of use of the LabOne User Interface the experiments are not only quick to set up, but most importantly, they provide high-quality, precise data. The MFIA is a great example of a tool that inspires and helps to shape tomorrow. Get in touch with our Impedance Team to discuss your ideas!

 

Many thanks to Tim Ashworth for inspiration, support and discussions on the subject!