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Process Measures

Process Measures

“Successfully performing a task is an impressive skill where the human is capable of. After all, every action is based on a past, takes place at the start in the present and then largely set in the uncertain future. What makes the dynamics of human action so special is that people apparently is able to account for a degree of unpredictability which always determines the success of the future outcome of the action co-determined”. 

Measured results can be broadly divided into two categories: outcome measures and process measures.

Outcome measures: in the English literature, performance measures are measured at different levels. 

Firstly, there are measuring instruments at the level of functions (ICF, 2001): strength, mobility/agility, endurance and speed, often with norm and criterion references as well as motion analyzes at the level of angle measurements of joints. This also includes ADL and borg scales, they measure, for example, fatigue, exertion or shortness of breath. Then there are measures at the level of the activities, such as development tests and skills tests. These clinical measures are valuable for recording treatment baseline, monitoring recovery and evaluating outcomes at the outcome level. The initial and final judgment is often determined by an outcome measure, but without having insight into the underlying processes. So far, we have been satisfied with the outcome measure as a measure of recovery and not how recovery or behavior is achieved.

Process measurements measure at a different level of description than performance measures. They are measurements that measure movements (kinematics) or forces (kinetics) in order to gain insight into how an action is brought about.

The kinematics describes movements of the body: the spatio-temporal change of body segments. At this measurement level, movements can be registered with inertial sensors, writing tablets or visual tracking systems. Subsequently, the variability (fluctuations) of movements is often quantified with non-linear analysis techniques (such as spectral analysis and entropy or linear analysis techniques such as signal-to-noise ratio and coefficient of variance) to determine underlying movement processes, the flexibility, coordination and stability of the neuromotor system.

With SoapSynergy you no longer have to perform these non-linear analysis techniques yourself, this is already being done. This results in the user being able to immediately use the insight into these underlying movement processes and apply them in practice.