Table 3.

Summary table of techniques with the new approach

Techniques	Advantages	Limitations	Refs.
Supervised	High success rates Interpretation of results	Limited number of anomalous samples: Unbalanced data base Health specialist presence required for data labeling Inability to characterize all anomalies	[34, 93–102]
Semi- Supervised	Normal samples available Ability to detect unknown anomalies	Since the postural pattern may be composed of different normal states, the normal boundary is wide Expert knowledge required in case of wanting to label different normal states	[19, 67, 103–114]
Unsupervised	No data labeling required Detection of unknown anomalies Applicable to large data sets	Increased tendency to false positives Lack of interpretation Normal data are grouped in clusters assumption	[92, 117–119, 122, 123, 125–127, 129–137]
Unsupervised	No data labeling required Detection of unknown anomalies Applicable to large data sets	Increased tendency to false positives Lack of interpretation Normal data are grouped in clusters assumption	[92, 117–120, 122–127, 129–138]