PMC:2944670 / 14348-19548 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/2944670","sourcedb":"PMC","sourceid":"2944670","source_url":"https://www.ncbi.nlm.nih.gov/pmc/2944670","text":"Human–computer interaction\nA related issue is how to improve the performance and reliability of current BCIs, which are characterized by noisy and low-bit-rate outputs. A promising possibility is the use of modern HCI principles to explicitly take into account the noisy and lagged nature of the BCI control signals to adjust the dynamics of the interaction as a function of the reliability of user's control capabilities. Such a HCI approach can also include the ability to “degrade gracefully” as the inputs become increasingly noisy (Williamson, 2006).\nHuman–computer interaction principles can lead to a new generation of BCI assistive devices by designing more suitable and comfortable interfaces that will speed up interaction, as demonstrated by the recent virtual keyboard “Hex-O-Spell” (Müller and Blankertz, 2006; Williamson et al., 2009). Regarding interaction and control of complex devices like neuroprostheses and mobile robots (or wheelchairs), it has recently been shown how shared autonomy techniques can drastically enhance the performance and robustness of a brain-controlled wheelchair (Vanacker et al., 2007; Galán et al., 2008; Millán et al., 2009). In a shared autonomy framework, the outputs of the BCI are combined with the information about the environment (obstacles perceived by the robot sensors) and the robot itself (position and velocities) to better estimate the user's intent. Some broader issues in human–machine interaction are discussed in Flemisch et al. (2003), where the H-Metaphor is introduced, suggesting that interaction should be more like riding a horse, with notions of “loosening the reins”, allowing the system more autonomy.\nShared autonomy (or shared control) is a key component of future hybrid BCI as it will shape the closed-loop dynamics between the user and the brain-actuated device such that tasks are able to be performed as easily as possible. As mentioned above, the idea is to integrate the user's mental commands with the contextual information gathered by the intelligent brain-actuated device so as to help the user to reach the target or override the mental commands in critical situations. In other words, the actual commands sent to the device and the feedback to the user will adapt to the context and inferred goals. In such a way, shared control can make target-oriented control easier, can inhibit pointless mental commands, and can help determine meaningful motion sequences (e.g., for a neuroprostheses). Examples of shared control applications are neuroprostheses such as robots and wheelchairs (Millán et al., 2004b, 2009; Vanacker et al., 2007; Galán et al., 2008; Tonin et al., 2010), as well as smart virtual keyboards (Müller and Blankertz, 2006; Wills and MacKay, 2006; Williamson et al., 2009), and other AT software with predictive capabilities.\nThe issue of improving the user interface is not a new problem; in addition some of the issues such as error rate and time taken to make a selection are not new in the general area of AT. The emphasis has mainly been on improving controllability and accuracy. Applications designed for BCI should be able to use different methods of BCI control, account for individual differences, optimize the user interface and incorporate artificial intelligence techniques. Simulation techniques can provide helpful information about the expected usability of a system. For instance, Biswas and Robinson (2007) describes a simulator which incorporates models of the application, interface and user to predict the performance of assistive technology devices.\nFinally, until fairly recently, the focus of software design and evaluation has been on usability and functionality in what are referred to as instrumental qualities. Current trends emphasize non-instrumental aspects of interface design and evaluation. These can be separated into the three categories; hedonics (concerned with [un]pleasant sensations), esthetics, and pleasure/fun (Mahlke, 2005). This development might be seen as attempting to establish the basics first before fine-tuning the details later. Nevertheless, Tractinsky et al. (2000) demonstrates that the perception of how usable a system is increases as visual esthetics of the system increases, although its actual usability remains unchanged. A valid question to ask, then, is whether BCI application design and evaluation can and should follow the same pattern of developing usable systems first before “targeting” the non-instrumental qualities. Given the current limitations of BCIs, how much of the existing knowledge of HCI design and evaluation can be applied to BCIs? It depends on the purpose of the application and how much control is required for the application to be used. Computer applications for BCI might be divided into three broad categories – programs for communication, tools for functional control, and entertainment applications. Entertainment programs can further be subdivided into games, tools for creativity and interactive media. The focus of evaluation for communication and functional applications should be on usability and functionality, while the focus of entertainment applications should be on pleasure and entertainment.","divisions":[{"label":"title","span":{"begin":0,"end":26}},{"label":"p","span":{"begin":27,"end":555}},{"label":"p","span":{"begin":556,"end":1674}},{"label":"p","span":{"begin":1675,"end":2828}},{"label":"p","span":{"begin":2829,"end":3574}}],"tracks":[{"project":"TEST0","denotations":[{"id":"20877434-220-228-475992","span":{"begin":1144,"end":1148},"obj":"[\"18621580\"]"},{"id":"20877434-157-165-475993","span":{"begin":2636,"end":2640},"obj":"[\"18621580\"]"},{"id":"20877434-226-234-475994","span":{"begin":2745,"end":2749},"obj":"[\"16792304\"]"}],"attributes":[{"subj":"20877434-220-228-475992","pred":"source","obj":"TEST0"},{"subj":"20877434-157-165-475993","pred":"source","obj":"TEST0"},{"subj":"20877434-226-234-475994","pred":"source","obj":"TEST0"}]},{"project":"0_colil","denotations":[{"id":"20877434-18621580-475992","span":{"begin":1144,"end":1148},"obj":"18621580"},{"id":"20877434-18621580-475993","span":{"begin":2636,"end":2640},"obj":"18621580"},{"id":"20877434-16792304-475994","span":{"begin":2745,"end":2749},"obj":"16792304"}],"attributes":[{"subj":"20877434-18621580-475992","pred":"source","obj":"0_colil"},{"subj":"20877434-18621580-475993","pred":"source","obj":"0_colil"},{"subj":"20877434-16792304-475994","pred":"source","obj":"0_colil"}]},{"project":"2_test","denotations":[{"id":"20877434-18621580-38386975","span":{"begin":1144,"end":1148},"obj":"18621580"},{"id":"20877434-18621580-38386976","span":{"begin":2636,"end":2640},"obj":"18621580"},{"id":"20877434-16792304-38386977","span":{"begin":2745,"end":2749},"obj":"16792304"}],"attributes":[{"subj":"20877434-18621580-38386975","pred":"source","obj":"2_test"},{"subj":"20877434-18621580-38386976","pred":"source","obj":"2_test"},{"subj":"20877434-16792304-38386977","pred":"source","obj":"2_test"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"TEST0","color":"#ba93ec","default":true},{"id":"0_colil","color":"#93eca0"},{"id":"2_test","color":"#ec939f"}]}]}}