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artificial neural network lab-nnet  (ActiGraph llc)

 
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    Structured Review

    ActiGraph llc artificial neural network lab-nnet
    Bottom and middle panels show 2-min 30-sec of second-by-second counts from the vertical acceleration signal. Top panel shows observer-identified activities. Using the <t>lab-nnet</t> and simple regression approaches the five distinct activities are grouped into minute intervals (bottom panel), resulting in inaccurate MET estimates. In free-living environments it may be more appropriate to identify where bouts of activity start and stop (middle panel) and estimate METs for specific activity bouts.
    Artificial Neural Network Lab Nnet, supplied by ActiGraph llc, 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/result/artificial neural network lab-nnet/product/ActiGraph llc
    Average 90 stars, based on 1 article reviews
    artificial neural network lab-nnet - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "A Method to Estimate Free-Living Active and Sedentary Behavior from an Accelerometer"

    Article Title: A Method to Estimate Free-Living Active and Sedentary Behavior from an Accelerometer

    Journal: Medicine and science in sports and exercise

    doi: 10.1249/MSS.0b013e3182a42a2d

    Bottom and middle panels show 2-min 30-sec of second-by-second counts from the vertical acceleration signal. Top panel shows observer-identified activities. Using the lab-nnet and simple regression approaches the five distinct activities are grouped into minute intervals (bottom panel), resulting in inaccurate MET estimates. In free-living environments it may be more appropriate to identify where bouts of activity start and stop (middle panel) and estimate METs for specific activity bouts.
    Figure Legend Snippet: Bottom and middle panels show 2-min 30-sec of second-by-second counts from the vertical acceleration signal. Top panel shows observer-identified activities. Using the lab-nnet and simple regression approaches the five distinct activities are grouped into minute intervals (bottom panel), resulting in inaccurate MET estimates. In free-living environments it may be more appropriate to identify where bouts of activity start and stop (middle panel) and estimate METs for specific activity bouts.

    Techniques Used: Activity Assay

    Lab-nnet, Soj-1x, Soj-3x and three traditional regression models compared to direct observation (DO) (mean (95% CI))
    Figure Legend Snippet: Lab-nnet, Soj-1x, Soj-3x and three traditional regression models compared to direct observation (DO) (mean (95% CI))

    Techniques Used:

    Lab-Nnet, Soj-1x and Soj-3x estimates for each participant. Model estimates for each participant compared to direct observation. The closer the point falls to the line of identity, the closer the estimate is to direct observation. Lab-nnet: open squares, soj-1x: open triangles, soj-3x: filled circles.
    Figure Legend Snippet: Lab-Nnet, Soj-1x and Soj-3x estimates for each participant. Model estimates for each participant compared to direct observation. The closer the point falls to the line of identity, the closer the estimate is to direct observation. Lab-nnet: open squares, soj-1x: open triangles, soj-3x: filled circles.

    Techniques Used:



    Similar Products

    artificial neural network lab-nnet  (ActiGraph llc)
    90
    ActiGraph llc artificial neural network lab-nnet
    Bottom and middle panels show 2-min 30-sec of second-by-second counts from the vertical acceleration signal. Top panel shows observer-identified activities. Using the <t>lab-nnet</t> and simple regression approaches the five distinct activities are grouped into minute intervals (bottom panel), resulting in inaccurate MET estimates. In free-living environments it may be more appropriate to identify where bouts of activity start and stop (middle panel) and estimate METs for specific activity bouts.
    Artificial Neural Network Lab Nnet, supplied by ActiGraph llc, 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/result/artificial neural network lab-nnet/product/ActiGraph llc
    Average 90 stars, based on 1 article reviews
    artificial neural network lab-nnet - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Bottom and middle panels show 2-min 30-sec of second-by-second counts from the vertical acceleration signal. Top panel shows observer-identified activities. Using the lab-nnet and simple regression approaches the five distinct activities are grouped into minute intervals (bottom panel), resulting in inaccurate MET estimates. In free-living environments it may be more appropriate to identify where bouts of activity start and stop (middle panel) and estimate METs for specific activity bouts.

    Journal: Medicine and science in sports and exercise

    Article Title: A Method to Estimate Free-Living Active and Sedentary Behavior from an Accelerometer

    doi: 10.1249/MSS.0b013e3182a42a2d

    Figure Lengend Snippet: Bottom and middle panels show 2-min 30-sec of second-by-second counts from the vertical acceleration signal. Top panel shows observer-identified activities. Using the lab-nnet and simple regression approaches the five distinct activities are grouped into minute intervals (bottom panel), resulting in inaccurate MET estimates. In free-living environments it may be more appropriate to identify where bouts of activity start and stop (middle panel) and estimate METs for specific activity bouts.

    Article Snippet: In a laboratory calibration study our group recently developed an artificial neural network (lab-nnet) to estimate METs from second-by-second ActiGraph TM (ActiGraph LLC, Pensacola, Florida) accelerometer output ( 37 ).

    Techniques: Activity Assay

    Lab-nnet, Soj-1x, Soj-3x and three traditional regression models compared to direct observation (DO) (mean (95% CI))

    Journal: Medicine and science in sports and exercise

    Article Title: A Method to Estimate Free-Living Active and Sedentary Behavior from an Accelerometer

    doi: 10.1249/MSS.0b013e3182a42a2d

    Figure Lengend Snippet: Lab-nnet, Soj-1x, Soj-3x and three traditional regression models compared to direct observation (DO) (mean (95% CI))

    Article Snippet: In a laboratory calibration study our group recently developed an artificial neural network (lab-nnet) to estimate METs from second-by-second ActiGraph TM (ActiGraph LLC, Pensacola, Florida) accelerometer output ( 37 ).

    Techniques:

    Lab-Nnet, Soj-1x and Soj-3x estimates for each participant. Model estimates for each participant compared to direct observation. The closer the point falls to the line of identity, the closer the estimate is to direct observation. Lab-nnet: open squares, soj-1x: open triangles, soj-3x: filled circles.

    Journal: Medicine and science in sports and exercise

    Article Title: A Method to Estimate Free-Living Active and Sedentary Behavior from an Accelerometer

    doi: 10.1249/MSS.0b013e3182a42a2d

    Figure Lengend Snippet: Lab-Nnet, Soj-1x and Soj-3x estimates for each participant. Model estimates for each participant compared to direct observation. The closer the point falls to the line of identity, the closer the estimate is to direct observation. Lab-nnet: open squares, soj-1x: open triangles, soj-3x: filled circles.

    Article Snippet: In a laboratory calibration study our group recently developed an artificial neural network (lab-nnet) to estimate METs from second-by-second ActiGraph TM (ActiGraph LLC, Pensacola, Florida) accelerometer output ( 37 ).

    Techniques: