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Acceleration wave of some exercises have more than one peak in one repetition.
For examples, two proximity peaks occur in one period of exercise TC, BP and OP.
Considering that each motion period is usually between 1.5 to 4.5 seconds, we take
the algorithm as the following:
(1) Search the peak point in the data stream in length of 2.5 seconds.
(2) If the interval between two adjacent peak points is less than 1 second, the later
peak point is canceled.
(3) If the interval between two adjacent peaks is between 1 to 1.5 seconds, and one
peak value is less than 70% of the other one, the minor peak is canceled.
The average accuracy rate of this method of splitting sequence is up to 98%. And for
some exercises such as BC, TC, LR and FL, it can be up to 100%.
3
Recognition Algorithm
Traditional DTW Algorithms can be seen in [8]
.
In this paper, the data captured by a
3-axial accelerometer is a 3-dimension (3D) time series. Though acceleration of x, y
and z-axis can be done respectively using standard DTW, 3D-DTW usually gets good
performance [12]. Given 3-axial acceleration reference series
T
R
=
{,
Rx
Rx
,
Rx
;
Ry
,
Ry
,
Ry
;
Rz
,
Rz
,
Rz
1
2
M
1
2
M
1
2
M
and test series ,
,
T
T
=
{,
Tx
Tx
,
Tx
;
Ty
,
Ty
,
Ty
;
Tz
,
Tz
,
Tz
1
2
N
1
2
N
1
2
N
the distance function is defined as
(1)
2
2
2
Dist i j
(,
) (
=
Rx
−
Tx
)(
+
Ry
−
Ty
)(
+
Rz
−
Tz
).
i
j
i
j
i
j
The warping path then gives the minimum normalized total warping distance
between
R
and
T
1
(,) min
(2)
DTW
RT
=
Dist
( ,
w
w
.
k
k
w
i
j
where
w
is the warping path,
w
is the length of
w
.
The global constraint conditions on the admissible warping paths can not only
speed up the DTW computation but also prevent the pathological alignments by
globally controlling the route of a warping path. Itakura parallelogram [14] is adopted
in this paper, which describes a region that constrains the slope of a warping path.
Reference template building is a main factor to the recognition rate of DTW.
Usually selecting only one example for each class as reference template cannot obtain
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