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Personalizing Energy Expenditure Estimation Usinga Cardiorespiratory Fitness PredicateMarco Altini, Julien Penders, Oliver...
A Sedentary Society
Disease TrendsObesity Trends
DiabetesHypertensionMetabolic SyndromeCardiovascular DiseaseObesity
WearableSensorsMeasureManage
Objective Physical Activity Monitoring
Walking biking Running Sedentary HouseholdMotionintensityEnergyExpenditureEEACC
Walking uphill Biking Walking stairsMotionintensityEnergyExpenditureEEACC
Walking Biking Running Sedentary Household StairsHeartRateEnergyExpenditureEEHR
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart Rate...
EEEE2 Subjects – Same Body SizeSame Energy Expenditure
HRHR2 Subjects – Same Body SizeDifferent Fitness Level -> Different HR
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart Rate...
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart Rate...
Study Design
16O2CO2Indirect Calorimeter
17ECG NecklaceACCHR
1829 Subjects, 48 ActivitiesHousehold Sport
VO2 max tests (gold standard)Sub-maximal testsNon-exercise testsCardiorespiratory Fitness AssessmentHR at a certain Worklo...
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart Rate...
Heart RateRunning10 km/hFitUnfitHeart RateNormalizationRestContext-Based Personalization
Heart RateContext-Based PersonalizationRunning10 km/hRestFitUnfitHeart RateNormalization
Heart RateContext-Based PersonalizationRestFitUnfitWalkingHR 4 km/hHR 5 km/hHR 6 km/hRunning10 km/h
Walking SpeedEstimatorActivityRecognition HR WalkingHR at RestHeart RateFeaturesAccelerometerFeaturesAnthropometricFeature...
120 140 160 180 200120140160180200Measured Normalization FactorPreidictedNormalizationFactor130 140 150 160 170 180-30-20-...
EEEE2 Subjects – Same Body SizeSame Energy Expenditure
HRHR2 Subjects – Same Body SizeDifferent Fitness Level -> Different HR
Normalized HR – Qualitative EvaluationNormalized HR-> Better EE Estimates
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart Rate...
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesLying downSedentaryEnergyExpenditureHeart RateNormalized HR...
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesLying downSedentaryEnergyExpenditureHeart RateNormalized HR...
Normalized HR – Quantitative EvaluationdynamicwalkingrunningbikingRMSE 1.02 kcal/min0.60kcal/min1.13kcal/min1.25kcal/min1....
AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesLying downSedentaryEnergyExpenditureHeart RateHeart RateNor...
Normalized HR – Quantitative EvaluationdynamicwalkingrunningbikingRMSE 0.81 kcal/min28% 33%29%3%26%0.60kcal/min0.58kcal/mi...
MotivationsSedentary SocietyDisease Trends
LimitationsInaccuracyOne Model Does Not Fit AllMotivations
NormalizationActivities of Daily LivingLimitationsMotivationsInter-Individual Differences
NormalizationLimitationsMotivationsPersonalized Models
Personalizing Energy Expenditure Estimation Usinga Cardiorespiratory Fitness PredicateMarco Altini, Julien Penders, Oliver...
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Personalizing Energy Expenditure Estimation Using a Cardiorespiratory Fitness Predicate

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Presentation for Pervasive Health 2013.

Paper Abstract: Accurate Energy Expenditure (EE) estimation is key in understanding how behavior and daily physical activity (PA) patterns affect health, especially in today’s sedentary society. Wearable accelerometers (ACC) and heart rate (HR) sensors have been widely used to monitor physical activity and estimate EE. However, current EE estimation algorithms have not taken into account a person’s cardiorespiratory fitness (CRF), even though CRF is the main cause of inter-individual variation in HR during exercise. In this paper we propose a new algorithm, which is able to significantly reduce EE estimate error and inter-individual variability, by automatically modeling CRF, without requiring users to perform specific fitness tests. Results show a decrease in Root Mean Square Error (RMSE) between 28 and 33% for walking, running and biking activities, compared to state of the art activity-specific EE algorithms combining ACC and HR.

Personalizing Energy Expenditure Estimation Using a Cardiorespiratory Fitness Predicate

  1. 1. Personalizing Energy Expenditure Estimation Usinga Cardiorespiratory Fitness PredicateMarco Altini, Julien Penders, Oliver Amft
  2. 2. A Sedentary Society
  3. 3. Disease TrendsObesity Trends
  4. 4. DiabetesHypertensionMetabolic SyndromeCardiovascular DiseaseObesity
  5. 5. WearableSensorsMeasureManage
  6. 6. Objective Physical Activity Monitoring
  7. 7. Walking biking Running Sedentary HouseholdMotionintensityEnergyExpenditureEEACC
  8. 8. Walking uphill Biking Walking stairsMotionintensityEnergyExpenditureEEACC
  9. 9. Walking Biking Running Sedentary Household StairsHeartRateEnergyExpenditureEEHR
  10. 10. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart RateActivity-Specific Energy ExpenditureModels
  11. 11. EEEE2 Subjects – Same Body SizeSame Energy Expenditure
  12. 12. HRHR2 Subjects – Same Body SizeDifferent Fitness Level -> Different HR
  13. 13. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart RateActivity-Specific Energy ExpenditureModels
  14. 14. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart RateActivity-Specific Energy ExpenditureModelsPersonalizedHeart RateNormalization
  15. 15. Study Design
  16. 16. 16O2CO2Indirect Calorimeter
  17. 17. 17ECG NecklaceACCHR
  18. 18. 1829 Subjects, 48 ActivitiesHousehold Sport
  19. 19. VO2 max tests (gold standard)Sub-maximal testsNon-exercise testsCardiorespiratory Fitness AssessmentHR at a certain Workload -> Fitness
  20. 20. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart RateActivity-Specific Energy ExpenditureModelsPersonalizedHeart RateNormalizationHR at a certain Workload -> Fitness
  21. 21. Heart RateRunning10 km/hFitUnfitHeart RateNormalizationRestContext-Based Personalization
  22. 22. Heart RateContext-Based PersonalizationRunning10 km/hRestFitUnfitHeart RateNormalization
  23. 23. Heart RateContext-Based PersonalizationRestFitUnfitWalkingHR 4 km/hHR 5 km/hHR 6 km/hRunning10 km/h
  24. 24. Walking SpeedEstimatorActivityRecognition HR WalkingHR at RestHeart RateFeaturesAccelerometerFeaturesAnthropometricFeaturesHeart RateNormalizationFactorHeart Rate NormalizationFactor EstimatorAge, HeightAutomatic Normalization Factor Estimation
  25. 25. 120 140 160 180 200120140160180200Measured Normalization FactorPreidictedNormalizationFactor130 140 150 160 170 180-30-20-100102030Normalization FactorResidualsAutomatic Normalization Factor EstimationRMSE 8.3 bpm
  26. 26. EEEE2 Subjects – Same Body SizeSame Energy Expenditure
  27. 27. HRHR2 Subjects – Same Body SizeDifferent Fitness Level -> Different HR
  28. 28. Normalized HR – Qualitative EvaluationNormalized HR-> Better EE Estimates
  29. 29. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesActivity 1 ModelActivity N ModelEnergyExpenditureHeart RateNormalized HR – Quantitative Evaluation
  30. 30. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesLying downSedentaryEnergyExpenditureHeart RateNormalized HR – Quantitative EvaluationHouseholdWalkingBikingRunning
  31. 31. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesLying downSedentaryEnergyExpenditureHeart RateNormalized HR – Quantitative EvaluationHouseholdWalkingBikingRunning
  32. 32. Normalized HR – Quantitative EvaluationdynamicwalkingrunningbikingRMSE 1.02 kcal/min0.60kcal/min1.13kcal/min1.25kcal/min1.38kcal/min
  33. 33. AccelerometerFeaturesActivity RecognitionAnthropometricFeaturesLying downSedentaryEnergyExpenditureHeart RateHeart RateNormalizationNormalized HR – Quantitative EvaluationHouseholdWalkingBikingRunning
  34. 34. Normalized HR – Quantitative EvaluationdynamicwalkingrunningbikingRMSE 0.81 kcal/min28% 33%29%3%26%0.60kcal/min0.58kcal/min1.13kcal/min0.81kcal/min1.25kcal/min0.89kcal/min1.38kcal/min0.92kcal/min
  35. 35. MotivationsSedentary SocietyDisease Trends
  36. 36. LimitationsInaccuracyOne Model Does Not Fit AllMotivations
  37. 37. NormalizationActivities of Daily LivingLimitationsMotivationsInter-Individual Differences
  38. 38. NormalizationLimitationsMotivationsPersonalized Models
  39. 39. Personalizing Energy Expenditure Estimation Usinga Cardiorespiratory Fitness PredicateMarco Altini, Julien Penders, Oliver AmftThank you

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