Detection of tactile-based error-related potentials (ErrPs) in human-robot interaction

Abstract

Robot learning based on implicitly extracted error detections (e.g., EEG-based error detections) has been well-investigated in human-robot interaction (HRI). In particular, the use of error-related potential (ErrP) evoked when recognizing errors is advantageous for robot learning when evaluation criteria cannot be explicitly defined, e.g., due to the complex behavior of robots. In most studies, erroneous behavior of robots were recognized visually. In some studies, visuo-tactile stimuli were used to evoke ErrPs or a tactile cue was used to indicate upcoming errors. To our knowledge, there are no studies in which ErrPs are evoked when recognizing errors only via the tactile channel. Hence, we investigated ErrPs evoked by tactile recognition of errors during HRI. In our scenario, subjects recognized errors caused by incorrect behavior of an orthosis during the execution of arm movements tactilely. EEG data from eight subjects was recorded. Subjects were asked to give a motor response to ensure error detection. Latency between the occurrence of errors and the response to errors was expected to be short. We assumed that the motor related brain activity is timely correlated with the ErrP and might be used from the classifier. To better interpret and test our results, we therefore tested ErrP detections in two additional scenarios, i.e., without motor response and with delayed motor response. In addition, we transferred three scenarios (motor response, no motor response, delayed motor response). Response times to error was short. However, high ErrP-classification performance was found for all subjects in case of motor response and no motor response condition. Further, ErrP classification performance was reduced for the transfer between motor response and delayed motor response, but not for the transfer between motor response and no motor response. We have shown that tactilely induced errors can be detected with high accuracy from brain activity. Our preliminary results suggest that also in tactile ErrPs the brain response is clear enough such that motor response is not relevant for classification. However, in future work, we will more systematically investigate tactile-based ErrP classification.

EEG and EMG dataset for the detection of errors introduced by an active orthosis device

“…These conclusions are very preliminary based on an analysis of only one subject. Our further analysis (Kim and Kirchner, 2023 ) showed some subjects with strong ErrP, weak P300, and a clearly visible ErrP in the grand average. We hope that the provided dataset and detailed information about the experimental setup will allow its replication enabling the research community to systematically investigate the relationship between odd-event detection and erroneous event evaluation evoked in the brain.…”

“…We observed a first negativity around 250 ms followed by a positivity between 300 ms and 500 ms and a further negativity around 600 ms. Results for all subjects and grand average ERP analysis for this dataset can be found in Kim and Kirchner ( 2023 ).…”

“…Therefore, investigating whether tactile detection of incorrect behavior in an exoskeleton or orthosis evokes similar event-related potentials (ERPs) as visually observed behavior is of interest. This information can be used to correct the incorrect behavior perceived by the patient [for initial results of this published dataset and further discussion on utilizing different modalities for transferring error information, see Kim and Kirchner ( 2023 )].…”