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Table 4 Heuristic cadence thresholds (steps/min) for relatively-defined moderate and vigorous intensity based on segmented regression and ROC curve analyses

From: Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study

    

Age Groups (years)

  

Intensity Level

Intensity Indicator

Measure

Group 1

(21–30)

Group 2

(31–40)

Group 3

(41–50)

Group 4

(51–60)

Moderate Intensity

≥ 64%HRmax

Threshold (steps/min)

120

120

115

110

Se

87.5

80.0

82.7

66.7

Sp

86.2

87.1

81.1

79.6

PPV

48.6

51.4

47.2

50.5

NPV

97.9

96.2

95.8

88.4

Accuracy

86.4

96.2

95.8

88.4

≥ 40%HRR

Threshold (steps/min)

120

120

115

110

Se

91.8

82.4

85.0

83.9

Sp

89.6

89.1

83.7

82.9

PPV

62.5

60.0

56.0

57.1

NPV

98.3

96.2

95.8

95.0

Accuracy

90.0

88.0

84.0

83.1

≥ 12 RPE

Threshold (steps/min)

120

120

115

110

Se

76.7

61.2

68.0

67.0

Sp

90.6

92.0

88.0

86.5

PPV

68.1

74.3

72.5

71.4

NPV

93.7

86.2

85.6

83.9

Accuracy

87.7

83.5

81.7

80.0

Vigorous Intensity

≥ 77%HRmax

Threshold (steps/min)

135

130

125

120

Se

55.6

69.2

82.3

78.6

Sp

97.0

93.9

90.0

87.3

PPV

35.7

33.3

32.6

23.9

NPV

98.6

98.6

98.9

98.8

Accuracy

95.8

92.9

89.5

86.9

≥ 60%HRR

Threshold (steps/min)

135

130

125

120

Se

60.0

62.5

76.2

78.6

Sp

97.3

94.2

90.5

87.3

PPV

42.9

37.0

89.5

23.9

NPV

98.6

97.9

37.1

98.8

Accuracy

96.1

92.6

89.5

86.9

≥ 14 RPE

Threshold (steps/min)

135

130

125

120

Se

50.0

63.2

61.9

81.0

Sp

98.0

94.8

89.5

89.2

PPV

95.5

92.9

87.6

88.6

NPV

57.1

44.4

30.2

37.0

Accuracy

97.3

97.5

97.0

98.4

  1. Trade-offs in terms of Se Sensitivity, Sp Specificity, PPV Positive Predictive Value, NPV Negative Predictive Value, and overall accuracy between the thresholds derived from the segmented regression and the ROC Receiver Operating Characteristic analyses were considered. The finally selected heuristic thresholds purposely reflected a favored tolerance for false negative versus false positive classifications