These headsets boast much quicker and easier installation and removal times of 3-5 min, in addition to being wireless. This device also has low weight and a battery life of up to 12 hours. Such devices have the advantage of being more user and consumer-friendly making them well-suited for situations where ergomomics and patient or participant movement is involved; as well as situations where scalability is of interest (e.g., having 30 students in a classroom all wearing an Emotiv, which would be highly impractical using a research device like Brainvision). Crucially, what set EPOC apart from the other available commercial devices is that at the time of its release it had one of the largest set of wireless electrodes, making it comparable to the electrode set sizes used in a significant part of literature representing research with traditional laboratory wired EEG equipment. Although there are some clear advantages to using a device like the Emotiv headsets in consumer/ecological and in some clinical settings, it does not come without its own challenges. Consumer grade EEG devices typically compromise data resolution for shorter setup time, affordability, and portability [21; 22; 23; 24; 25; 26]. Since portable headsets have less electrodes and channels than standard research-grade EEGs, scalp coverage and spatial resolution decrease [27]. The use of dry electrodes can also pose a problem as impedance can hinder the detection of electrical activity and lead to lower data values. This can be mitigated by using saline solution, but its effect is minimal compared to electro-conductive gel [24]. Overall, concerns around portable EEGs are centred on the accuracy and reliability of their data as compared to standard, research-grade EEGs. There is an important growing body of scientific literature investigating the Emotiv under different conditions utilizing various EEG signatures such as the P300 [24] which has demonstrated its poor reliability/accuracy compared to research-grade devices. However, other studies have demonstrated that EPOC can accurately detect P300 and N200 [26; 27]. That said, the study from [PERSON] et al. (2017) utilized a modified Emotiv with electrodes that had been upgraded to research-grade quality [26] which may have played a significant role in the success of the Emotiv application. Another study from [PERSON] et al. (2015) [28] further demonstrated that the morphology of EEG signals such as the P1, N1, P2, N2, and P3 were highly correlated between the Emotiv and research-grade Neuroscan system; however there were some differences in the amplitude of the signal. Needless to say, there remains a disparity in the literature which requires more research to be done to elucidate the truth about the Emotiv. There are so many factors that may influence the success of an Emotiv application: Notably, the study by [PERSON] et al. (2012) [24] which reported poor quality of the Emotiv for detecting P300 utilized a visual odd-ball paradigm, whereas the studies that were more successful [26; 27; 28] utilized auditory odd-ball paradigms. Therefore, the modality of the task used to elicit the EEG signal may play an important role. However, a more recent study from [PERSON] (2021) [29] was able to successfully capture and utilize subject's P300 signal with reasonable accuracy for a brain-computer interface speller (a visual paradigm) when combined with machine learning such as support vector machines. A critical emerging issue related to wireless portable EEG devices such as EPOC is the application to personalized healthcare [30]. Personalization implies that the quality of repeated measurements of desired EEG features have an acceptable to optimal level of **precision** or **reliability** (i.e., _measurement or instrumental precision_) at the level of an individual (i.e., the so-called \"N-of-1\") (see [31]).