Development of a human-motion database for intelligent wearable robots

Abstract

Human-motion data need to be stored and processed to manage wearable robots. Given the considerable data volume associated with sensor data, we designed a database that efficiently stores sensor data from human motion and can be used by intelligent wearable robots. We designed a database for sensor data from human motions for use in intelligent wearable robots. We used functions to preprocess and transform the data into JSON files. Additionally, we created a function to store and process data files in the database. A database of human-motion data is necessary to determine whether robot movements (e.g., by wearable robots or robot simulations) are similar to those of humans. The most common methods for collecting motion data from people have been markerless optical systems. However, these methods are less accurate than motion capture using a non-optical system. We designed and
implemented a database to collect and store accurate human-motion data using a non-optical inertial motion-capture system. Our database can be applied to walking robots used for people with paraplegic disabilities who need walking assistance, and to robots and equipment that mimic human movements for people working in high-risk environments. Our system can also be applied to humanoid robotics.