Research and Sport - Unlock new data layer for further research, product development and performance optimization.

Senmotion provides a holistic approach to analyze real life data from different fields of application in relation to big data analytics. Ground reaction force patterns are influenced by numerous factors. In addition to basic parameters such as gait speed, age, gender, footwear and other factors, these include acute medical and chronic factors. In the latter case, pathological characteristics or abnormalities are compared to the gait pattern of healthy subjects. Many pathological or abnormal ground reaction force patterns are known to be caused by various diseases or injuries, therefore diagnosis based on these patterns plays a key role in health and medical care.

However, this finding contrasts with a very large number of diseases, particularly chronic diseases, directly associated with gait disorders, but it is not clear whether they are the compensation or the cause of an injury or damage. These also include chronic non-specific back pain or other arthritic changes. This ignorance has its origin in the current diagnosis and the current possibilities of data acquisition, which is not able to continuously register changes over a long period of time. At the same time, many individual measures are not queried and are not associated with the force pattern.

Our approach can combine long-term measurements outside the laboratory under real conditions with a direct link to our pattern database. Once used successfully as a medical device, Senmotion offers the possibility to be used in other fields of application. In professional sport, the same requirements apply as in the therapeutic or rehabilitative field. Athletes and patients need structured guidelines based on status-quo and longitudinal analyses for concrete training planning and control: Rehabilitation and therapy is just good training.