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peratech sp200 sensors  (Peratech Holdco)

 
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    Structured Review

    Peratech Holdco peratech sp200 sensors
    Metric comparison between Interlink and <t> Peratech sensors. </t>
    Peratech Sp200 Sensors, supplied by Peratech Holdco, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/peratech sp200 sensors/product/Peratech Holdco
    Average 86 stars, based on 1 article reviews
    peratech sp200 sensors - by Bioz Stars, 2026-03
    86/100 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:



    Similar Products

    peratech sp200 sensors  (Peratech Holdco)
    86
    Peratech Holdco peratech sp200 sensors
    Metric comparison between Interlink and <t> Peratech sensors. </t>
    Peratech Sp200 Sensors, supplied by Peratech Holdco, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/peratech sp200 sensors/product/Peratech Holdco
    Average 86 stars, based on 1 article reviews
    peratech sp200 sensors - by Bioz Stars, 2026-03
    86/100 stars
    		  Buy from Supplier

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    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: On the other hand, it is noteworthy that R 2 notably differs from one brand to another, with higher dispersion occurring in the Peratech SP200 sensors.

    Techniques: