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qtc sp200 sensors  (Peratech Holdco)

 
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    Structured Review

    Peratech Holdco qtc sp200 sensors
    Metric comparison between Interlink and Peratech sensors.
    Qtc Sp200 Sensors, supplied by Peratech Holdco, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/qtc+sp200+sensors/pmc11511561-132-32-33?v=Peratech+Holdco
    Average 90 stars, based on 1 article reviews
    qtc sp200 sensors - by Bioz Stars, 2026-07
    90/100 stars

    Images

    1) Product Images from "Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors"

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    Journal: Sensors (Basel, Switzerland)

    doi: 10.3390/s24206592

    Metric comparison between Interlink and Peratech sensors.
    Figure Legend Snippet: Metric comparison between Interlink and Peratech sensors.

    Techniques Used: Comparison

    Photographs of the mechanical setup. ( a ) Overview of the testbench; ( b ) Zoom-in photo depicting the linear motor for applying forces to the bunch of sensors. ( c ) Photograph of FSRs installed inside sensor holders, Peratech SP200 (yellow) and Interlink FSR402 (orange). ( d ) Zoom-in photo depicting the sensors inside the chamber and the spring for mechanical compliance. ( e ) Photograph of two side-by-side sensor holders showing the puck (top side) and the notch (bottom side). ( f ) Custom design element for holding aligned the sensor holders, and the spring. A FSR was placed near the element for comparison purposes.
    Figure Legend Snippet: Photographs of the mechanical setup. ( a ) Overview of the testbench; ( b ) Zoom-in photo depicting the linear motor for applying forces to the bunch of sensors. ( c ) Photograph of FSRs installed inside sensor holders, Peratech SP200 (yellow) and Interlink FSR402 (orange). ( d ) Zoom-in photo depicting the sensors inside the chamber and the spring for mechanical compliance. ( e ) Photograph of two side-by-side sensor holders showing the puck (top side) and the notch (bottom side). ( f ) Custom design element for holding aligned the sensor holders, and the spring. A FSR was placed near the element for comparison purposes.

    Techniques Used: Comparison

    Drift error ( d.e. ) at multiple input voltages for the Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.
    Figure Legend Snippet: Drift error ( d.e. ) at multiple input voltages for the Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.

    Techniques Used:

    Pearson Correlation Coefficient (PCC) for the drift error as a function of V o_null at multiple input voltages.
    Figure Legend Snippet: Pearson Correlation Coefficient (PCC) for the drift error as a function of V o_null at multiple input voltages.

    Techniques Used:

    Drift error ( d.e. ) measured at V i = 5 V with three superimposed trendlines. ( a ) Interlink FSR402, ( b ) QTC Peratech SP200.
    Figure Legend Snippet: Drift error ( d.e. ) measured at V i = 5 V with three superimposed trendlines. ( a ) Interlink FSR402, ( b ) QTC Peratech SP200.

    Techniques Used:

    Fit parameters for the drift error ( d.e. ) models at V i = 5 V.
    Figure Legend Snippet: Fit parameters for the drift error ( d.e. ) models at V i = 5 V.

    Techniques Used:

    Hysteresis error ( h.e. ) measured at multiple input voltage for Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.
    Figure Legend Snippet: Hysteresis error ( h.e. ) measured at multiple input voltage for Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.

    Techniques Used:

    Result of k -means clustering method using k = 2 for Peratech SP200 sensors at V i = 5 V.
    Figure Legend Snippet: Result of k -means clustering method using k = 2 for Peratech SP200 sensors at V i = 5 V.

    Techniques Used:

    Result of k -means clustering method using k = 3 for Peratech SP200 sensors at V i = 5 V.
    Figure Legend Snippet: Result of k -means clustering method using k = 3 for Peratech SP200 sensors at V i = 5 V.

    Techniques Used:

    Result of k -means clustering method using k = 4 for Peratech SP200 sensors at V i = 5 V.
    Figure Legend Snippet: Result of k -means clustering method using k = 4 for Peratech SP200 sensors at V i = 5 V.

    Techniques Used:

    Flowchart summarizing the process for measuring and assessing the hysteresis error in Peratech SP200 sensors.
    Figure Legend Snippet: Flowchart summarizing the process for measuring and assessing the hysteresis error in Peratech SP200 sensors.

    Techniques Used:



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    Image Search Results


    Metric comparison between Interlink and Peratech sensors.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Metric comparison between Interlink and Peratech sensors.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques: Comparison

    Photographs of the mechanical setup. ( a ) Overview of the testbench; ( b ) Zoom-in photo depicting the linear motor for applying forces to the bunch of sensors. ( c ) Photograph of FSRs installed inside sensor holders, Peratech SP200 (yellow) and Interlink FSR402 (orange). ( d ) Zoom-in photo depicting the sensors inside the chamber and the spring for mechanical compliance. ( e ) Photograph of two side-by-side sensor holders showing the puck (top side) and the notch (bottom side). ( f ) Custom design element for holding aligned the sensor holders, and the spring. A FSR was placed near the element for comparison purposes.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Photographs of the mechanical setup. ( a ) Overview of the testbench; ( b ) Zoom-in photo depicting the linear motor for applying forces to the bunch of sensors. ( c ) Photograph of FSRs installed inside sensor holders, Peratech SP200 (yellow) and Interlink FSR402 (orange). ( d ) Zoom-in photo depicting the sensors inside the chamber and the spring for mechanical compliance. ( e ) Photograph of two side-by-side sensor holders showing the puck (top side) and the notch (bottom side). ( f ) Custom design element for holding aligned the sensor holders, and the spring. A FSR was placed near the element for comparison purposes.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques: Comparison

    Drift error ( d.e. ) at multiple input voltages for the Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Drift error ( d.e. ) at multiple input voltages for the Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Pearson Correlation Coefficient (PCC) for the drift error as a function of V o_null at multiple input voltages.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Pearson Correlation Coefficient (PCC) for the drift error as a function of V o_null at multiple input voltages.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Drift error ( d.e. ) measured at V i = 5 V with three superimposed trendlines. ( a ) Interlink FSR402, ( b ) QTC Peratech SP200.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Drift error ( d.e. ) measured at V i = 5 V with three superimposed trendlines. ( a ) Interlink FSR402, ( b ) QTC Peratech SP200.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Fit parameters for the drift error ( d.e. ) models at V i = 5 V.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Fit parameters for the drift error ( d.e. ) models at V i = 5 V.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Hysteresis error ( h.e. ) measured at multiple input voltage for Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Hysteresis error ( h.e. ) measured at multiple input voltage for Interlink FSR402 ( a – c ) and QTC Peratech SP200 ( d – f ) sensors.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Result of k -means clustering method using k = 2 for Peratech SP200 sensors at V i = 5 V.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Result of k -means clustering method using k = 2 for Peratech SP200 sensors at V i = 5 V.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Result of k -means clustering method using k = 3 for Peratech SP200 sensors at V i = 5 V.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Result of k -means clustering method using k = 3 for Peratech SP200 sensors at V i = 5 V.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Result of k -means clustering method using k = 4 for Peratech SP200 sensors at V i = 5 V.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Result of k -means clustering method using k = 4 for Peratech SP200 sensors at V i = 5 V.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Flowchart summarizing the process for measuring and assessing the hysteresis error in Peratech SP200 sensors.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Usage of Machine Learning Techniques to Classify and Predict the Performance of Force Sensing Resistors

    doi: 10.3390/s24206592

    Figure Lengend Snippet: Flowchart summarizing the process for measuring and assessing the hysteresis error in Peratech SP200 sensors.

    Article Snippet: In order to obtain statistically representative results, the experimental tests in this study were performed on 48 Interlink FSR402 sensors manufactured by Interlink Electronics (Irvine, CA, USA) [ ] and on 48 QTC Peratech SP200 sensors manufactured by Peratech Holdco Limited (Sedgefield, UK) [ ].

    Techniques:

    Sensor model specifications

    Journal: Canadian Prosthetics & Orthotics Journal

    Article Title: Evaluating the Dynamic Performance of Interfacial Pressure Sensors at a Simulated Body-Device Interface

    doi: 10.33137/cpoj.v4i1.36059

    Figure Lengend Snippet: Sensor model specifications

    Article Snippet: 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).

    Techniques: