Bulk Calibration and Filtering

When the tactile sensors were initially tested without any form of individual element calibration, it was seen that some elements had higher sensitivity than others due to incon- sistencies in the PCB surface finish and the sandwiched material. This resulted in green patches appearing on the tactile pressure map even when there is no tumour underneath. This can be seen in the results presented in the evaluation section. The tumours were still identifiable since they appeared as distinct yellow-red spots on the pressure map, but the green patches can be distracting and confusing for the user, making it important to eliminate them. These patches could be eliminated by calibrating each individual sensor element to measure the true pressure, thereby cancelling the effects of the variation. However, this is a very tedious process, and it is preferable to avoid doing it. An alternative bulk calibration approach was developed as a solution that proved to work very well.

The bulk calibration process involves three quick steps that can be performed via the user interface right before using the sensor. The button for executing the next step is enabled only after completing the previous step as a means of ensuring that the steps are completed in the correct order. The progress of each step is displayed via the small progress bar in the calibration section. These steps are outlined below:

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1. Establish minimum force: This step is initiated by clicking on the “Set Min” button

on the user interface. Before clicking the button, the tactile sensor must be pressed very lightly (approximately 0.5 N) against the surface of the tissue in an area with no tumour. This step records the readings from all the elements for one second to establish the baseline reading for detecting tissue contact.

2. Establish maximum force: This step is initiated by clicking on the “Set Max” button

on the user interface. Before clicking the button, the tactile sensor must be pressed with the maximum allowable safe force (14 N with the large tactile sensors and 7 N with the small ones that translates to a 30 kPa pressure leaving a 7 kPa margin before tissue damage occurs [1]) against the surface of the tissue in an area with no tumour. This step records the readings from all the elements for one second to establish the reading for tissue contact with the maximum allowable safe force.

A separate force sensor must be used in the above steps to accurately establish the contact force. In a practical use scenario, this may be possible only when using a tissue phantom rather than the actual tissue being palpated, unless the instrument with the tactile sensor has a force sensor built into it. All of the element readings collected in each of these two steps is averaged to get a single value that represents the minimum and maximum contact force for the entire sensor.

A simple experiment was conducted to assess the accuracy of the average reading of all of the elements in representing the true total contact force after the two-step min–max calibration. The setup involved a commercial ATI Gamma force sensor underneath a block of Shore 00-10 silicone with no tumour, and the tactile sensor was pressed on top of the block. Comparing the average tactile sensor reading with the reading from the force sen- sor showed that the average reading can be used to predict the total contact force with an accuracy of at least 89% for both piezoresistive and capacitive sensors by using the mathe- matical model presented earlier, even though the individual elements have slightly different

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response. This experiment was also repeated with a porcine liver sample instead of the silicone block. It was found that the min–max calibration data obtained with the silicone block could be used to predict the total contact force on the liver sample with an accuracy of at least 82%. This demonstrates that the approach of using the average reading as an indicator of the total force is sufficiently accurate to provide useful kinaesthetic feedback and prevent tissue damage.

Since these first two steps may be cumbersome and/or inaccurate to be performed in the operating room, it can be performed when testing the sensor during the manufacturing pro- cess, before the sterilization step. Since the experiment above showed that the calibration performed on a silicone phantom still applies to real tissue, it is not necessary that these two steps be performed on the actual tissue that will be palpated. The two calibration values can be supplied with each sensor, and the visualization software can be easily modified to accept these predetermined values.

At this point, the force bar gets activated. The total contact force is displayed as a percentage, where 0% represents no contact, 1% represents the minimum contact force, and 100% represents the maximum allowable contact force. The mathematical model presented earlier is used along with the min–max calibration data to convert the average reading of the sensor to actual contact force. The force is displayed as a percentage instead of the actual force measurement since it is more intuitive to understand.

3. Live calibration: This step is initiated by clicking on the “Calibrate” button on the

user interface. This step must be performed on the actual tissue being palpated to obtain the best results. Before clicking the button, the tactile sensor must be gently resting against the surface of the tissue in an area with no tumour, such that the force bar still reads 0%. Once the button is pressed, the process lasts for 15 seconds, and the small progress bar is used to indicate the progress through the step. During this time, the user is expected to cycle the contact force two to three times between about 5% to about 95% as indicated by the force

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bar, and the software records the readings from each individual element separately.

The 450 samples of data collected during the calibration step are used to create a map of the change in the reading of each individual element as a function of the average reading of all the elements. To create this map, the difference between the minimum and maximum average readings established in the first two bulk calibration steps is divided into 50 equal intervals. The 450 samples for each element are then divided into 50 sets based on the interval that the corresponding average reading falls in. All of the samples in each of the sets is averaged to produce 50 equally-spaced calibration data points for each element as a function of the average reading. A three-point moving average filter is used on the 50 data points to smoothen any sharp variations. At this point, the entire calibration process is complete, and the check-boxes for activating compensation and filtering are enabled.

If the compensation check-box is checked, then the live calibration data is used to com- pensate for the variations in the sensitivity of the individual elements. The compensation process simply involves determining in which of the 50 intervals the current average read- ing falls in, and then subtracting the calibration data points corresponding to the next higher interval from the readings of each element. If this process results in an element’s pressure reading being negative, it is simply changed to zero. Performing this compensation was found to enable an underlying tumour to be seen very clearly since, for the same average reading, the readings from the elements on top of the tumour are significantly higher than what they would be if there was no tumour. When the compensation is enabled, the colour of the tactile pressure map no longer corresponds to the true element pressure. Instead, it represents how much higher the pressure on an element is than the average pressure on the entire sensor. Experiments show that since the elements on top of a tumour will experience about 15 kPa to 40 kPa higher pressure than the average, depending on the stiffness and depth of the tumour, the display sensitivity must be set to almost the maximum to enable the tumour to be seen as a green-red spot on the tactile map.