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VOLUME 4, ISSUE 1 

 2021 

 

RESEARCH ARTICLE 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 

Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

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1 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

 

 

 
RESEARCH ARTICLE 

 

EVALUATING THE DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS AT A 

SIMULATED BODY-DEVICE INTERFACE  

Hamilton M1,2, Sivasambu H2, Behdinan K3, Andrysek J1,2 * 
 

1 Institute of Biomedical Engineering, Faculty of Applied Science and Engineering, University of Toronto, Toronto, Canada.  
2 Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada.  
3 Department of Mechanical and Industrial Engineering, Faculty of Applied Science and Engineering, University of Toronto, Toronto, Canada. 

 

 

 

 

  

 

 

 

 

 

 

 

 
 

INTRODUCTION   

Pressure sensing in mobility assistive technology (MAT) 

can inform the fitting of patient-customized devices such as 

prostheses and orthoses. For example, lower-limb 

prosthetic setup can take multiple weeks from the first to the 

final optimized fitting.1 Each fitting session features both 

static (i.e. standing) and dynamic (i.e. walking) weight-

bearing assessments, where the clinician relies on their 

visual perception and fitting experience, as well as patient 

feedback to iteratively refine the fit and function of the 

device.1 Both static and dynamic assessments provide 

critical information, however dynamic assessments provide 

more pertinent information related to everyday mobility 

use.2 The integration of pressure-sensing into the MAT can 

help to quantify pressures at the MAT-body interface, 

affording clinicians more objective assessments, and thus 

improving overall fit and performance of the device.3,4 

There are several commercially available interfacial 

pressure sensors, with varying technologies such as force-

sensitive resistors, strain gauges, quantum tunneling 

composites, strain gauges and others.5,6 Most studies 

evaluating these sensors focus on static testing. The few 

sensor evaluation studies that have examined dynamic 

loading conditions, do not closely characterize the patterns 

of walking.7–9 Parmar et al. and Khodasevych et al. used 10 

 
OPEN  ACCESS Volume 4, Issue 1, Article No.4. 2021 

 

 

Journal Homepage: https://jps.library.utoronto.ca/index.php/cpoj/index 

 

ABSTRACT 

BACKGROUND: Pressure sensing at the body-device interface can help assess the quality of fit and 

function of assistive devices during physical activities and movement such as walking and running. 

However, the dynamic performance of various pressure sensor configurations is not well established. 

OBJECTIVE(S): Two common commercially available thin-film pressure sensors were tested to 

determine the effects of clinically relevant setup configurations focusing on loading areas, interfacing 

elements (i.e. ‘puck’) and calibration methods. 

METHODOLOGY: Testing was performed using a customized universal testing machine to simulate 

dynamic, mobility relevant loads at the body-device interface. Sensor performance was evaluated by 

analyzing accuracy and hysteresis. 

FINDINGS: The results suggest that sensor calibration method has a significant effect on sensor 

performance although the difference is mitigated by using an elastomeric loading puck. Both sensors 

exhibited similar performance during dynamic testing that agree with accuracy and hysteresis values 

reported by manufacturers and in previous studies assessing mainly static and quasi-static conditions. 

CONCLUSION: These findings suggest that sensor performance under mobility relevant conditions may 

be adequately represented via static and quasi-testing testing.  This is important since static testing is 

much easier to apply and reduces the burden on users to verify dynamic performance of sensors prior 

to clinical application. The authors also recommend using a load puck for dynamic testing conditions to 

achieve optimal performance. 

ARTICLE INFO 

Received: February 19, 2021 

Accepted: May 8, 2021 

Published: May 19, 2021 

CITATION 

Hamilton M, Sivasambu H, 

Behdinan K, Andrysek J. 

Evaluating the dynamic 

performance of interfacial 

pressure sensors at a simulated 

body-device interface. Canadian 

Prosthetics & Orthotics Journal. 

2021;Volume 4, Issue 1, No.4. 

https://doi.org/10.33137/cpoj.v4i

1.36059 

KEYWORDS 

Calibration, Interface Pressure, 

Pressure Sensor, Pressure 

Measurement, Prosthetics, 

Repeatability, Sensor Evaluation 

 

* CORRESPONDING AUTHOR:  

Jan Andrysek, PhD 

Bloorview Research Institute, Holland Bloorview Kids Rehabilitation 

Hospital, Toronto, Canada. 

Email: jandrysek@hollandbloorview.ca 

ORCID: https://orcid.org/0000-0002-4976-1228 

 

 

https://doi.org/10.33137/cpoj.v4i1.36059
https://jps.library.utoronto.ca/index.php/cpoj/index
https://doi.org/10.33137/cpoj.v4i1.36059
https://doi.org/10.33137/cpoj.v4i1.36059
mailto:jandrysek@hollandbloorview.ca
https://orcid.org/0000-0002-4976-1228


 

2 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
cycles of load application with 30 seconds on and 30 

seconds off to simulate dynamic wear of a prosthesis.6,10 

However, the typical walking cycles are much more dynamic 

repeating at approximately one Hertz (Hz) frequency.11 

Hence, the mobility-relevant dynamic performance of 

interfacial pressure sensors remains to be established.  

Aside from the loading patterns, previous research has 

shown that performance can greatly vary depending on the 

way a sensor is configured in its sensing application.9,10 The 

force-resistance relationship of a thin film sensor depends 

on factors such as sensor shape, geometry, and design, as 

well as the way by which the forces are applied to the 

sensor.12 In fact, sensor manufacturers recommend that 

sensors be tested and calibrated under conditions that 

closely match their application.12  However, this is difficult to 

do for MAT applications, due to the complex nature of the 

interface. For example sensor manufacturers recommend 

that the area of applied load be held constant at an area 

slightly smaller than the sensors’ sensing area.12–14 

However, such conditions are not representative of the 

dynamic conditions of a body-device interface, where the 

loading area fluctuates and typically is larger than the 

sensing area. Sensor performance has been shown to vary 

with the area of applied load, however, testing has not been 

performed under dynamic conditions,15 despite well 

documented differences in sensor performance under static 

and dynamic conditions.16 Previous research with piezo-

resistive sensors has reported a trade-off between the 

dynamic performance (hysteresis error) and the static 

sensitivity, as increased stiffness will alter the viscoelastic 

behavior causing hysteresis and reduce static  

sensitivity.17–19 Commercially available pressure mapping 

systems designed specifically for the MAT-body interface, 

such as the F-socket, utilize an array of sensors to provide 

pressure profiles over a large portion of the interface. 

However, these systems have limited clinical usage since 

they can be costly, bulky, cumbersome to apply, and suffer 

from performance issues including failure due to creasing; 

there is also a lack of information about their dynamic 

performance.5,18 As such, current understanding of dynamic 

performance of sensors in MAT-representative interfaces is 

limited, thus restricting the effective use of these sensors. 

The overall objective of this study was to evaluate the 

effects of previously identified setup conditions (load area 

and presence of an elastomeric interface ‘puck’) on the 

dynamic performance of two common commercial pressure 

sensors. A sub-objective of the study was to understand the 

effects of two calibration techniques on sensor 

performance, including calibrating under matched-area 

(MA) and simplified, generalized-area (GA) conditions. As 

such, this study aimed to establish conditions and protocols 

that simulate dynamic testing of interfacial pressure sensors 

at the body-device interface, and empirically inform the use 

of the sensors for improved performance.  

METHODOLOGY 

Testing was performed to assess the effect of area of 

applied load and sensor calibration method on sensor 

dynamic performance under two loading configurations: 

with and without a puck. The puck causes the force applied 

to the sensor to be concentrated over a particular area of 

the sensor.12 

SENSORS 

This study was performed on two commercially available 

sensors, the QTC™ SP200-10 sensor (Peratech Ltd, 

Richmond, North Yorkshire, UK) and the ThruMode™ FSR 

(Sensitronics, Bow, WA, USA). These sensors were 

selected due to their high performance and broad use in 

other studies.6,10 Table 1 displays sensor specifications. 

Table 1: Sensor model specifications 

Parameter 
QTC™      

SP200-10 

Half Inch 

ThruMode™ FSR 

Manufacturer Peratech Ltd. Sensitronics Inc. 

Sensing Diameter (mm) 10 12.7 

Thickness (mm) 0.45 0.43 

Claimed Operating Range (N) 0.1 to 20  0.26 to 26a 

Single Part Repeatability (%) N/Ab 5  

Part-to-Part Repeatability (%) 4.5  15   

 

a Reported as 0.3 – 30 psi, converted to N using sensing area.  
b Not reported. 

 

DATA ACQUISITION SYSTEM 

Time and force data were collected using the Instron Bluehill 

Universal software. Resistance values were collected using 

a Keithley 6500 6 ½ Digit Multimeter (DMM) (Tektronix, Inc., 

Beaverton, OR, USA) and Tektronix’s proprietary KickStart 

software (Tektronix, Inc., Beaverton, OR, USA). All data 

were collected at 500 Hz. Resistance, force, and time data 

were analyzed using MATLAB v19 (The MathWorks, Inc., 

Natick, MA, USA). 

TESTING APPARATUS 

An apparatus designed to simulate human tissue developed 

in a previous study evaluating pressure sensors under static 

conditions was used in this study.15 A 2 cm layer of soft 

translucent silicone (Renew® Silicone 10, Renew®, Easton, 

PA, USA), shown to mimic behavior of human tissue,20-22 

was placed over the Instron base platen. An Instron 5944 

Universal Testing System with a 100 N load cell (Instron, 

Norwood, MA, USA) applied loads up to 10 N. This force 

range was selected as it is within both sensor’s working 

range and represents forces and pressures applied at 

 the body-device interface in various biomedical 

applications.23, 24 

https://doi.org/10.33137/cpoj.v4i1.36059


 

3 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
Loading tip attachments (contact diameters of 5 mm, 8 mm, 

15 mm, and 25 mm) were 3D-printed (PLA White Material; 

Ultimaker 2 Printer; Ultimaker B.V., Netherlands) and press-

fit to the Instron’s upper compression platen. The 8 mm tip 

adhered to manufacturer recommendations for minimum 

coverage of FSR sensing area (i.e., load applicator 20% 

smaller than sensing diameter of sensor).12 This sizing 

prevented interactions with the spacer and adhesive 

surrounding the sensing area, while ensuring much of the 

sensing element was activated. The 5 mm tip represented 

conditions when a portion of the sensing area is loaded 

(e.g., point load). Clinically relevant conditions in which the 

loading area surpasses the sensing area are represented 

by the 15- and 25-mm diameter tips. 

To understand the effects of sensor configuration, a loading 

puck was used as per sensor manufacturers’ recomm-

endations under half of the conditions tested.12 A silicone 

loading puck (1.5 mm thickness, 8mm diameter, and 

durometer 60 shore a hardness) guaranteed the force was 

transferred entirely through the sensing area. The effect of 

the loading puck on the system’s phase and magnitude 

response was assumed to be negligible as the 

manufacturer recommends a silicone actuator to improve 

performance in cases of inconsistent force actuation;12 

consistent responses with the loading puck were confirmed 

in pilot testing. Previous work indicated the use of the 

loading puck and omission of a rigid backing produced the 

best repeatability for both sensors.15 Figure 1 displays a 

photo of the setup and a labelled schematic indicating 

sensor configuration with the loading puck. 

   

PROTOCOL 

Application Conditions 

To evaluate the effects of load area and elastomer puck 

presence on sensor dynamic performance, a full factorial 

experiment was conducted using eight application 

conditions: four loading tip areas, both with and without an 

elastomer puck. The order of application conditions was 

randomized to minimize potential testing bias. 

Sensor Conditioning 

Prior to testing each sensor, manufacturer guidelines for 

sensor conditioning were followed,13 in which 110% of the 

maximum test load (11 N) was applied to the sensor for 30 

seconds, and then removed for 30 seconds. This cycle was 

repeated four times. 

Sensor Calibration 

Prior to dynamic testing, a force sweep from 0 to 10 N was 

applied to the sensor at a loading rate of 0.67 N/s (i.e. 

loading duration of 15 s). This force sweep was repeated 

three times and the corresponding resistance and force 

data were curve-fit in MATLAB to characterize the sensor’s 

force-resistance curve for a given configuration (i.e. area 

and puck configuration).25 An exponential relationship (1) 

was selected to convert resistance output to pressure 

values for the subsequent tests based on manufacturer 

recommendations, literature, and best fit.12,25 

𝑦 = 𝑎𝑥−𝑏                                                             (1) 

  

 

Figure 1: Actual setup, labelled schematic showing configuration with loading puck, and photo of sensors: (i) Sensitronics, (ii) Peratech 

(i) (ii) 

Silicone (Tissue) 

Elastomer loading puck Sensor 

Loading tip attachments 

of varying area 

F
Instron

 

https://doi.org/10.33137/cpoj.v4i1.36059


 

4 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
Two different calibration methods were used: MA and GA 

calibration techniques. Though sensor manufacturers 

recommend calibration conditions that imitate sensor use, 

this is not always possible at the body-device interface (i.e., 

inconsistent actuation and area of applied load); 

showcasing the importance of the simplified GA calibration 

method. The MA calibration is a more accurate, time-

consuming method in which the exact configuration used 

during testing is matched during the calibration. The second 

method, GA calibration, is a time-saving approach where 

one configuration used during calibration is then applied to 

multiple configurations (i.e. different areas) during the 

experimental testing. For this study, both calibration 

methods were used to convert the same set of experimental 

data (sensor resistance) to force measurements, enabling a 

comparison between the used performance measures (i.e., 

Normalized root-mean squared error (NRMSE) and 

hysteresis error (HE)). Specifically, for the MA calibration, 

the calibration equation for each configuration was applied 

to the experimental data. For the GA calibration, only the 

calibration equation from the 8 mm puck was applied to 

each set of experimental data.    

SENSOR TESTING 

Hysteresis Testing 

Hysteresis is the difference in sensor output at the same 

force when the sensor is being loaded and unloaded and is 

commonly used to assess the performance of FSRs.24,26 To 

understand the sensor’s dynamic performance and identify 

hysteresis effects, the sensor was loaded from 0 to 10 N 

and then unloaded to 0 N at rates of 10 N/s (duration of two 

seconds). This was repeated 3 times. This loading rate was 

selected to analyze the hysteresis effects under conditions 

similar to dynamic loading: one second each of loading and 

unloading in the test is comparable to the average gait cycle 

time of approximately one second.27 

Dynamic Testing 

A square wave profile was applied to the sensor: loaded to 

10 N, held for 1 second, unloaded to 0.5 N, held for 1 

second, and repeated 10 times. The profile was intended to 

roughly approximate the weight bearing and non-weight 

bearing loading patterns during walking gait.  

ANALYSIS 

Sensor performance was evaluated by analyzing accuracy 

and hysteresis. Researchers identified these performance 

measures during the evaluation of an interface 

force/pressure sensor.10,28 Accuracy errors, evaluated in 

both hysteresis and gait testing, was calculated using a 

normalized root-mean square error (NRMSE). The NRMSE, 

is calculated by dividing RMSE by applied force of 10 N and 

then converting the value to a percentage (2): 

 

NRMSE =
RMSE

F ̅
∗ 100%  

 

 

 (2) 

Hysteresis error (HE) was calculated by taking the 

maximum difference in sensor output (loading versus 

unloading) for a given force level. The hysteresis difference, 
Funloading – Floading, was calculated at each force from 0.5 

to 10 N at increments of 0.1 N. The equation used to 

calculate HE (3): 

  

HE =
Funloading − Floading

F ̅ 
∗ 100% 

 

(3) 

The hysteresis error was normalized by dividing by the 

maximum force of 10 N, and then converted to a 

percentage. For each trial, the hysteresis error was 

calculated at the force with the greatest hysteresis 

difference. An additional measure of sensor performance 

was the coefficient of variation (CV).9,26 Typically, clinical 

applications require a CV of less than 10%.6 

An analysis of variance (ANOVA) was used to compare the 

effects of calibration method and puck on the NRMSE and 

HE for each sensor model (i.e., Peratech and Sensitronics). 

All main effects, 2-way and 3-way interactions were 

evaluated with p<0.05 indicating significance. Insignificant 

effects were then removed from the model, and significant 

main effects, 2 and 3-way interactions were reported. A 

paired t-test was performed on each set of results (i.e., 

NRMSE, HE) to quantify differences in sensor performance. 

JMP® Pro 14 software was used (SAS Institute Inc., Cary, 

NC, USA). 

RESULTS 

DYNAMIC HYSTERESIS TESTING 

The force applied versus time plots for the Peratech and 

Sensitronics sensors are displayed in Figure 2 and Figure 

3. The force applied versus force measured representing 

the hysteresis curves for the Peratech and Sensitronics 

sensors are displayed in Figure 4 and Figure 5. Subplots 

are grouped by configuration: no elastomer puck (NP) and 

with elastomer puck (YP); as well as calibration method: MA 

and GA. Line colours distinguish the area of applied load, 

and line styles distinguish the trial number, as shown in the 

legend. NRMSE and HE values for the applications 

conditions are displayed in Table 2. 

In Figure 2 and Figure 3, the applied force waveform is 

displayed in green on the plot, as indicated in the legend. 

These figures provide a visualization of the sensor’s 

accuracy in each configuration. Overall, the Peratech 

sensor exhibits higher accuracy than the Sensitronics 

https://doi.org/10.33137/cpoj.v4i1.36059


 

5 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
sensor. The Sensitronics sensor signal exhibits more noise. 

The addition of the puck shows a significant improvement in 

sensor accuracy, especially in the GA calibration data. 

Without a puck, the GA calibration data accuracy reaches 

roughly 50% for the larger areas with both sensors. A dead 

band appears for the Peratech sensor in the NP condition 

with areas larger than the sensing area (15 and 25 mm), 

where no force is measured until approximately 3.5 N. In the 

MA calibration conditions, following the dead band, the data 

reaches 10 N because each data set was calibrated 

individually, with a different set of resistance values 

corresponding the force values for each configuration. 

 Overall, as seen in Figure 4 and Figure 5, the hysteresis 

error was significantly less for the Peratech sensor, 

compared to the Sensitronics sensor (p=0.01). For both 

sensors, the addition of the puck appeared to reduce 

hysteresis errors. The dead band described above can also 

be seen in these hysteresis plots. For both sensors, the 

NRMSE is below 10% for the majority of cases, with most 

exceptions occurring under conditions without a loading 

puck at the larger areas. While the HE is under 10% for most 

conditions for the Peratech sensor, all the HE values for the 

Sensitronics sensor are above 10% recommended for use 

in clinical applications.6 

Table 2: Hysteresis and NRMSE results. 

 

Config 
Diameter 

(mm) 

Peratech (%) Sensitronics (%) 

MA 

Calibration 

GA 

Calibration 

MA 

Calibration 

GA 

Calibration 

NRMSE HE NRMSE HE NRMSE HE NRMSE HE 

NP 

5 2.6 ± 1.3 8.4 ± 1.7 32.8 ± 0.1 15.9 ± 4.6 5.4 ± 0.5 15.9 ± 1.4 7.8 ± 1.7 20.6 ± 2.8 

8 2.0 ± 0.2 8.6 ± 0.4 2.0 ± 0.2 8.6 ± 0.4 5.4 ± 2.1 16.0 ± 4.5 5.4 ± 2.1 16.0 ± 4.5 

15 11.1 ± 0.2 23.2 ± 15.3 46.8 ± 0.1 12.8 ± 3.9 9.9 ± 0.2 43.2 ± 8.6 57.3 ± 0.1 39.8 ± 14.6 

25 11.0 ± 0.1 12.2 ± 1.6 52.2 ± 0.3 11.5 ± 4.2 11.7 ± 2.1 48.3 ± 7.3 54.9 ± 0.3 38.6 ± 13.2 

YP 

5 4.8 ± 0.4 13.4 ± 0.8 9.2 ± 1.0 15.2 ± 0.6 5.3 ± 1.6 16.8 ± 2.9 9.9 ± 0.4 18.7 ± 2.7 

8 1.7 ± 0.4 7.8 ± 1.4 1.7 ± 0.4 7.8 ± 1.4 9.5 ± 0.9 25.4 ± 1.4 9.5 ± 0.9 25.4 ± 1.4 

15 2.5 ± 0.2 9.5 ± 0.4 2.8 ± 0.2 8.0 ± 0.1 7.3 ± 1.8 19.8 ± 2.5 9.8 ± 0.7 20.9 ± 1.9 

25 2.0 ± 0.3 8.8 ± 0.9 3.0 ± 0.1 6.6 ± 1.0 6.6 ± 2.2 19.0 ± 5.4 8.7 ± 1.1 22.4 ± 3.8 

 

 

Figure 2: Force vs. time plots for two-second hysteresis tests for Peratech sensor using MA and GA calibration methods. 

iii) NP Generalized-Area Calibration iv) YP Generalized-Area Calibration

Legend

(Area-Trial #)

05-1

05-2

05-3

08-1

08-2

08-3

15-1

15-2

15-3

25-1

25-2

25-3

Applied 

Force

F
o

rc
e

 (
N

)

8

6

4

2

0

10

F
o

rc
e

 (
N

)

8

6

4

2

0

10

F
o

rc
e

 (
N

)

8

6

4

2

0

10

F
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rc
e

 (
N

)

8

6

4

2

0

10

i) NP Matched-Area Calibration

Time (s)

0 0.5 1 1.5 2

ii) YP Matched-Area Calibration

Time (s)

0 0.5 1 1.5 2

Time (s)

0 0.5 1 1.5 2

Time (s)

0 0.5 1 1.5 2

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Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 

 

 

Figure 3: Force vs. time plots for two-second hysteresis tests for Sensitronic sensor using MA and GA calibration methods.  

i) NP Matched-Area Calibration ii) YP Matched-Area Calibration

iv) YP Generalized-Area Calibrationiii) NP Generalized-Area Calibration

F
o

rc
e

 (
N

)
8

6

4

2

0

10

Time (s)

0 0.5 1 1.5 2

F
o

rc
e
 (

N
)

8

6

4

2

0

10

Time (s)

0 0.5 1 1.5 2

F
o

rc
e

 (
N

)

8

6

4

2

0

10

F
o

rc
e

 (
N

)

8

6

4

2

0

10

Time (s)

0 0.5 1 1.5 2

Time (s)

0 0.5 1 1.5 2

 

Figure 4: Force measured vs. force applied plots for two-second hysteresis tests for Peratech using MA and GA calibration methods. 

Force Applied (N)

0 2 4 6 8 10

F
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a
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N

)

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i) NP Matched-Area Calibration ii) YP Matched-Area Calibration

iii) NP Generalized-Area Calibration iv) YP Generalized-Area Calibration

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https://doi.org/10.33137/cpoj.v4i1.36059


 

7 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 

DYNAMIC TESTING 

NRMSE values for both sensors under the different 

application conditions are displayed in Table 3. With the MA 

calibration method, the NRMSE is below 10% for both 

sensors, meeting the desired threshold for accuracy in 

clinical applications.6 Using the GA calibration method with 

a puck, the CV across the areas averaged 8.8 ± 3.8 % for 

both sensors. Without a puck for the GA calibration method, 

CV values exceed 100% for the larger areas for both 

sensors. 

 

In the GA condition, similar trends showing the effects of the 

area can be seen in the hysteresis (Table 2) and dynamic 

(Table 3) results.  In general, the NRMSE is lowest for GA 

with matched areas (8mm diameter loading tip and 8mm 

sensor area) and accuracy is decreased with higher 

NRMSE values for the smaller (5mm) diameter loading tip. 

This is most evident for the Peratech sensor. NRMSE is 

further increased for the two larger diameters (15 and 

25mm). 

 

Figure 5: Force measured vs. force applied plots for two-second hysteresis tests for Sensitronics using MA and GA calibration methods. 

i) NP Matched-Area Calibration ii) YP Matched-Area Calibration

iii) NP Generalized-Area Calibration iv) YP Generalized-Area Calibration

F
o

rc
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a
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 (
N

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6

4

2

0

10

F
o

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e

a
s
u

re
d

 (
N

) 8

6

4

2

0

10

Force Applied (N)

0 2 4 6 8 10

Force Applied (N)

0 2 4 6 8 10

Force Applied (N)

0 2 4 6 8 10

Force Applied (N)

0 2 4 6 8 10

F
o

rc
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N

)

5

0

10

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N

)

5

0

10

Table 3: Dynamic testing - NRMSE 

Configuration Area 
Peratech Sensor Sensitronics Sensor 

MA 
Calibration 

GA 
Calibration 

MA 
Calibration 

GA 
Calibration 

NP 
 

05 3.7 ± 1.3 112.9 ± 2.8 8.9 ± 1.6 6.8 ± 0.9 

08 6.2 ± 0.3 6.2 ± 0.3 5.0 ± 0.8 5.0 ± 0.8 

15 6.6 ± 0.8 118.0 ± 5.9 8.4 ± 0.4 317.9 ± 18.3 

25 6.1 ± 0.2 558.3 ± 16.6 5.4 ± 0.6 185.6 ± 6.5 

YP 

05 4.8 ± 0.1 17.2 ± 0.0 4.2 ± 0.8 11.5 ± 1.3 

08 4.9 ± 0.6 4.9 ± 0.6 6.8 ± 0.4 6.8 ± 0.4 

15 3.7 ± 0.2 6.3 ± 0.3 5.9 ± 0.7 6.3 ± 0.8 

25 2.9 ± 0.1 6.8 ± 0.5 7.3 ± 0.1 10.8 ± 1.2 

 

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 F

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 2

. 

https://doi.org/10.33137/cpoj.v4i1.36059


 

8 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
DISCUSSION 

This study aimed to uniquely establish the methods and 

baseline data for relevant setup and calibration 

configurations and testing under dynamic loading patterns, 

for two commonly used pressure sensors. The study 

applied dynamic testing conditions that, compared to 

previous work, were much more representative of patterns 

present in human walking gait. The findings suggest that 

both sensors exhibited similar performance during dynamic 

testing that agree with accuracy and hysteresis values 

reported by manufacturers and in previous studies 

assessing mainly static and quasi-static conditions.  In 

addition, the calibration method was found to significantly 

influence sensor performance, although much less so when 

an elastomeric loading puck was applied to the sensor.  

Researchers have cited hysteresis and accuracy as key 

requirements of a successful interfacial sensor, although 

performance under dynamic conditions is often a 

limitation.10,26 Overall, the dynamic performance of the two 

commercial sensors is quite similar, however the Peratech 

generally exhibited better performance (i.e. higher 

accuracy) with lower hysteresis and dynamic testing errors. 

The calibration method, as found in previous work, had a 

significant impact on the dynamic sensor performance.15 

However, GA calibration can be used in place of MA 

calibration when using a loading puck to ensure the load is 

transmitted through the sensing area, regardless of the load 

applicator size. GA calibration is significantly easier and 

more practical to perform.  

The NRMSE values reported in this study agree with the 

accuracy values reported in the study by Parmar et al6  

ranging from 94.8 to 96.0% (equivalent to an error of 4.0 to 

5.2%) for the Peratech sensor and 90.8 to 94.0% 

(equivalent to an error of 6.0 to 9.2%) for the Sensitronics 

sensor. These values are within the range of the errors seen 

for the 8 mm loading tip applicator conditions using MA 

calibration. Similarly, the hysteresis error observed for the 

Peratech sensor with the 8 mm loading tip applicator 

conditions using MA calibration agrees with the 

manufacturer reported hysteresis error of 8.5%.29 Finally, 

the CV of 8.8 ± 3.8% for dynamic testing with the loading 

puck agrees with previous works performing static testing 

under the same conditions (7.6 ± 3.6%).15These findings 

provide new evidence suggesting that the sensor 

performance is not adversely affected by dynamic loading 

that is at the frequencies relevant to mobility. It further 

suggests that the performance is sufficient for most clinical 

applications.6 

Previous studies have suggested potential performance 

trade-offs between static and dynamic performance,17,18,30 

however for the sensors and conditions tested here this did 

not appear to be the case. In part this may be because the 

loading frequencies associated with gait mobility are not 

high enough to adversely affect dynamic performance. 

Alternatively, the findings may be influenced by the type of 

sensor technology or material used. Nevertheless, for gait 

related MAT applications the findings have important 

implications on the utilization of the thin film sensors, 

suggesting that static testing and calibration as suggested 

by manufacturers might be adequately sufficient, without 

the need for further dynamic testing. This is important, since 

whereas static testing can simply be performed with a dead 

weight, dynamic testing requires specialized equipment that 

is not readily accessible. Implementation of objective 

measures produced by pressure sensors and similar 

systems are typically confined to research settings due to 

their cost and lack of portability.31,32 However, the potential 

simplification of testing protocols and assurance of their 

relevance to dynamic testing, is important for feasibility in 

the case of the use of these sensors in research as well as 

clinical realms.   

A limitation to the study is the assumption of uniformity in 

tissue loading. Testing performed included a uniform layer 

of silicone simulating tissue at the body-device interface. In 

real life, the anatomy of a limb includes inconsistencies in 

tissue properties and bony prominences that can affect 

compliance and curvature. Additionally, effects of frictional 

shear forces, temperature, and curvature were not 

examined in this work, but have been shown to affect 

pressure measurements. Additionally, it is possible that a 

portion of the measured errors may be associated with the 

dynamic response of the testing machine setup, rather than 

sensor performance. The limits of the sensors should also 

be explored in dynamic applications, including higher cycle 

frequencies. A faster cycle time, (i.e. 1 second instead of 2 

seconds) would be more representative of the dynamics of 

normal gait.  Finally, the feasibility of incorporating a loading 

puck in a body-device interface or in an actual clinical 

application was not assessed here. Future work will need to 

consider feasibility and performance of adding pucks, 

including their design (i.e. thickness, hardness) and effects 

on aspects such as comfort and application time.  

CONCLUSION 

This study develops and tests a unique protocol for the 

dynamic testing of pressure sensors at the body-device 

interface, and addresses concerns with existing approaches 

including applicator size, loading profile, and sensor 

conditioning and calibration. Overall, when using sensor 

configurations recommended by manufacturers both 

sensors exhibited performance sufficient for use in clinical 

applications. The foundational knowledge established by 

this work reveals that existing thin film pressure sensors 

may be a suitable tool for measuring pressures at the body 

device interface, such as prosthetic sockets and orthosis, 

and can do so for dynamic conditions such as gait. Future 

https://doi.org/10.33137/cpoj.v4i1.36059


 

9 

Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
work in this area should examine the effects of additional 

properties unique to the body-device interface.   

ACKNOWLEDGEMENTS 

The authors would like to thank those who reviewed and 

supported the development of this work. 

DECLARATION OF CONFLICTING 

INTERESTS 

The authors declare that they have no competing interests.  

AUTHOR CONTRIBUTION 

Megan Hamilton: contributed to the study concept and 

design, data gathering, analysis and interpretation, and 

contributed to the drafting of the manuscript. 

Harry Sivasambu: contributed to data analysis and 

interpretation, drafting of the manuscript, and read and 

approved the final manuscript. 

Kamran Behdinan: contributed to the study concept and 

design, contributed to the drafting of the manuscript, and 

read and approved the final manuscript. 

Jan Andrysek: contributed to the study concept and 

design, analyzed and interpreted data, contributed to the 

drafting of the manuscript and read and approved the final 

manuscript. 

SOURCES OF SUPPORT 

This work was supported by the EMHSeed program from 

the University of Toronto.  

ETHICAL APPROVAL 

Ethical approval was not needed for this study. 

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Hamilton M, Sivasambu H, Behdinan K, Andrysek J. Evaluating the dynamic performance of interfacial pressure sensors at a simulated body-device interface. 
Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.4. https://doi.org/10.33137/cpoj.v4i1.36059 

ISSN: 2561-987X DYNAMIC PERFORMANCE OF INTERFACIAL PRESSURE SENSORS 

Hamilton et al. 2021 CPOJ 

 
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