A working environment which elicits positive emotions in employees is vital for employee retention, engagement and productivity. Wearable sensors provide the means to objectively measure the emotional responses of employees in the workplace in real-time. The study aim was to perform a preliminary investigation into the validity of two multimodal systems to classify employee's emotional responses to positive, neutral or negative video stimuli: (1) using wearable electroencephalography (EEG) in combination with video-based facial expression analysis (FEA), and (2) using a wearable galvanic skin response (GSR) device in combination with video-based FEA. Five office employees each watched three short video clips at three time points during their regular work shifts while wearing EEG sensors on the forehead and GSR sensors on the middle and index fingers of their non-dominant hand with their face in view of a webcam. Russel's circumplex model of affect was used to determine participant's emotional responses to the video clips. The GSR device showed greater accuracy than the EEG device at detecting arousal responses to the video stimuli, with agreement, precision, and recall values of 87%, 100% and 80%, respectively, compared to 53%, 62%, and 80% for the EEG device. The FEA/EEG and FEA/GSR circumplex models were both able to accurately detect positive emotions elicited from video stimuli with levels of agreement and recall greater than 73%. Precision for the FEA/EEG model to detect positive stimuli was lower due to misclassification of 40% of both negative and neutral stimuli as positive. Precision values for both circumplex models were very low for detecting negative emotions. The results suggest that the EEG and GSR devices may be capable of detecting arousal when used alone, and detecting positive emotions when used in combination with video-based FEA in real-time in the workplace.