falldetectionsystem

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falldetectionsystem [2014/12/09 08:09]
mroriz
falldetectionsystem [2014/12/09 08:11]
mroriz [4.1.3 Experiment 3]
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 In the third experiment we validate the thresholds found in the second experiment with accelerometer data that contain values of fall. For that we put the accelerometer at the height of the pocket of pants, and throw it on the floor for 6 times and between each time we performed different activities such as stand, sit, walk. We collected the accelerometer data during 2 minutes at a frequency of one sample per half second for a total of 239 samples. We calculated the mean of the module and then we created a function that detect the falls in the same way that the Esper Rule, with the Fall Threshold. In the third experiment we validate the thresholds found in the second experiment with accelerometer data that contain values of fall. For that we put the accelerometer at the height of the pocket of pants, and throw it on the floor for 6 times and between each time we performed different activities such as stand, sit, walk. We collected the accelerometer data during 2 minutes at a frequency of one sample per half second for a total of 239 samples. We calculated the mean of the module and then we created a function that detect the falls in the same way that the Esper Rule, with the Fall Threshold.
  
-{{pmu%20relatorio%202_files:image020.png?536x31}}As result, all the 6 times the function detects the fall.+{{image020.png?536x31}}As result, all the 6 times the function detects the fall.
  
-{{pmu%20relatorio%202_files:image022.png?527x175}}Figura 9: Experiment 3 Data+{{image022.png?527x175}}Figura 9: Experiment 3 Data
  
 === Formalization === === Formalization ===
  
-·         Objective: validate the thresholds found in the second experiment with accelerometer data that contain values of fall, creating a function fall(x) that detect the falls in the same way that the Esper Rule.+  * Objective: validate the thresholds found in the second experiment with accelerometer data that contain values of fall, creating a function fall(x) that detect the falls in the same way that the Esper Rule.
  
-·         Set-up: accelerometer at the height of the pocket of pants, and throw it on the floor for 6 times and between each fall we performed different activities such as stand, sit, walk. We collected the accelerometer data during 2 minutes at a frequency of one sample per half second for a total of 239 samples.+  * Set-up: accelerometer at the height of the pocket of pants, and throw it on the floor for 6 times and between each fall we performed different activities such as stand, sit, walk. We collected the accelerometer data during 2 minutes at a frequency of one sample per half second for a total of 239 samples.
  
-·         Parameters to be varied: activities performed: none, walk, sit, stand and fall+  * Parameters to be varied: activities performed: none, walk, sit, stand and fall
  
-·         Metrics:+  * Metrics:
  
-{{pmu%20relatorio%202_files:image024.png?145x20}} {{pmu%20relatorio%202_files:image026.png?516x31}}+{{image024.png?145x20}} {{image026.png?516x31}}
  
-Where {{pmu%20relatorio%202_files:image028.png?246x24}}  +Where {{image028.png?246x24}} 
- +
-·         Results: As result, all the 6 times the function detects the fall.+
  
 +  * Results: As result, all the 6 times the function detects the fall.
 ===== 4.2 Test of thresholds ===== ===== 4.2 Test of thresholds =====
  
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