Fig 1.
The distribution of PD patients based on the total Unified Parkinson’s Disease Rating Scale (UPDRS).
The modified score is used to evaluate the symptoms, 0 being no symptoms, and 5 denoting full bed rest or using a wheelchair.
Table 1.
Demographic data of cohort used in study.
Fig 2.
General workflow of the machine learning system from [31].
Figure adapted from the original source.
Fig 3.
The orientation of the smartphone during 20 step walking tests: X, Y and Z axes denote up-down, right-left and forth-back directions, respectively.
Positive Z axis denotes the walking direction, when walking a straight line.
Fig 4.
Example signal from raw ang low-pass filtered walking signal, from the x-axis accelerometer.
Fig 5.
One step cycle from a filtered accelerometer signal in the vertical direction (from heel strike to heel strike).
The peaks (green dot) and troughs (red dots) were identified as the local maxima and minima above and below a threshold, respectively. Thresholds are indicated by the green and red dotted lines. Two segments, Ai and Bi were measured for each step i. A denotes the time from the beginning of a heel strike to a toe-off. B denotes the time from the toe-off to the next heel strike.
Fig 6.
Accuracy plotted for 5–100 features selected with the mRMR algorithm and using the Support Vector Machine classifier, logistic regression and linear discriminant analysis.
The highest result for each classifier is marked with an x.
Table 2.
Detailed classification results (accuracy) obtained with Support Vector Machine, logistic regression, and linear discriminant analysis for minimum Redundancy Maximum Relevance sets between 5–20 features.
Table 3.
Number of selected features with different classification and feature selection methods.
Table 4.
Classification of individual steps with nine classifiers and three feature selection methods.
Fig 7.
Statistical testing results for Cochran’s Q test and post-hoc test with pairwise comparison of individual step classification.
P-values above 0.01 are marked with green background, and the best five classifiers compared are marked with blue background and white text. The classifier names with the highest accuracy are also bolded. The classifier pairs are placed in the order of the p-value.
Table 5.
Overall classification of subjects based on classification of individual steps and majority voting.
Five highest performing classifiers were selected for comparison of overall classification. Columns on the right side present the number of subjects classified in each category.