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Table 1 Features used for identifying the inertial sensors

From: Automatic identification of inertial sensor placement on human body segments during walking

  

Feature

 

Description

a

ω

α

 RMS of the

-magnitude

RMS{ ||a||}

RMS{ ||ω||}

RMS{ ||α||}

-x-component

RMS{ a x }

RMS{ ω x }

RMS{ α x }

-y-component

RMS{ a y }

RMS{ ω y }

RMS{ α y }

 Variance of the

-magnitude

Var{ ||a||}

Var{ ||ω||}

Var{ ||α||}

-x-component

Var{ a x }

Var{ ω x }

Var{ α x }

-y-component

Var{ a y }

Var{ ω y }

Var{ α y }

-z-component

Var{ a z }

Var{ ω z }

Var{ α z }

 Sum of cc’s of a sensor with all other sensors of the

-magnitude

Σ cc{ ||a||}

Σ cc{ ||ω||}

Σ cc{ ||α||}

-x-component

Σ cc{ a x }

Σ cc{ ω x }

Σ cc{ α x }

-y-component

Σ cc{ a y }

Σ cc{ ω y }

Σ cc{ α y }

-z-component

Σ cc{ a z }

Σ cc{ ω z }

Σ cc{ α z }

 The maximum value of the cc’s of a sensor with all other sensors of the

-magnitude

Max{cc{ ||a||}}

Max{cc{ ||ω||}}

Max{cc{ ||α||}}

-x-component

Max{cc{ a x }}

Max{cc{ ω x }}

Max{cc{ α x }}

-y-component

Max{cc{ a y }}

Max{cc{ ω y }}

Max{cc{ α y }}

-z-component

Max{cc{ a z }}

Max{cc{ ω z }}

Max{cc{ α z }}

 The inter-axis cc’s of a sensor between the

-x- and y-axes

cc{ a x ,a y }

cc{ ω x ,ω y }

cc{ α x ,α y }

-x- and z-axes

cc{ a x ,a z }

cc{ ω x ,ω z }

cc{ α x ,α z }

-y- and z-axes

cc{ a y ,a z }

cc{ ω y ,ω z }

cc{ α y ,α z }

  1. All 57 (19 ·3) features are given as input to the decision tree learner. The C4.5 algorithm automatically chooses the features that split the data most effectively.