Examples are disclosed that relate to methods and systems for classifying a surface type. One example provides a system comprising a wearable device comprising at least one force sensor, and a computing device having a processor and associated memory storing instructions executable by the processor. The instructions are executable by the processor to, during a training phase, receive training data including a plurality of training data pairs. Each training data pair includes force sensor training data received from the at least one force sensor, or from a simulation or observation, and a label indicating at least one of a plurality of defined surface types. An AI model is trained to predict a classified surface type based on run-time force sensor data. The run-time force sensor data is input into the trained AI model to thereby cause the AI model to output a predicted classification of a run-time surface type.

Examples are disclosed that relate to methods and systems for classifying a surface type. One example provides a system comprising a wearable device comprising at least one force sensor, and a computing device having a processor and associated memory storing instructions executable by the processor. The instructions are executable by the processor to, during a training phase, receive training data including a plurality of training data pairs. Each training data pair includes force sensor training data received from the at least one force sensor, or from a simulation or observation, and a label indicating at least one of a plurality of defined surface types. An AI model is trained to predict a classified surface type based on run-time force sensor data. The run-time force sensor data is input into the trained AI model to thereby cause the AI model to output a predicted classification of a run-time surface type.

Examples are disclosed that relate to methods and systems for classifying a surface type. One example provides a system comprising a wearable device comprising at least one force sensor, and a computing device having a processor and associated memory storing instructions executable by the processor. The instructions are executable by the processor to, during a training phase, receive training data including a plurality of training data pairs. Each training data pair includes force sensor training data received from the at least one force sensor, or from a simulation or observation, and a label indicating at least one of a plurality of defined surface types. An AI model is trained to predict a classified surface type based on run-time force sensor data. The run-time force sensor data is input into the trained AI model to thereby cause the AI model to output a predicted classification of a run-time surface type.