Promoting autonomy in a smart home environment with a smarter interface

Abstract

In the not too distant future, the median population age will tend towards 65; an age at which the need for dependency increases. Most older people want to remain autonomous and self-sufficient for as long as possible. As environments become smarter home automation solutions can be provided to support this aspiration. The technology discussed within this paper focuses on providing a home automation system that can be controlled by most users regardless of mobility restrictions, and hence it may be applicable to older people. It comprises a hybrid Brain-Computer Interface, home automation user interface and actuators. In the first instance, our system is controlled with conventional computer input, which is then replaced with eye tracking and finally a BCI and eye tracking collaboration. The systems have been assessed in terms of information throughput; benefits and limitations are evaluated.

Electroencephalogram based Brain Computer Interface System Analysis

“…Joining together the features for existing games with mind controlling competencies has been subject to huge number of researches for example, [38] which have a tendency should furnish a multi-brain stimulation experience. This feature game is known as BrainArena.…”

Design of an EEG Acquisition System for Embedded Edge Computing

“…Taking this use of EEG one step forward multiple articles [15][16][17][18][19][20][21] discuss integrating EEG with the Internet of Things (IOT) to control different devices in a smart home using protocols like Message Queue Telemetry Transport (MQTT) and Extensible Messaging and Presence Protocol (XMPP). These interfaces can further be used to improve healthcare and the general living standard of differently-abled people and in-turn make everyone's life easier.…”

“…A similar algorithm is applied to control the fan, however in that case, changes in a combination of frequency and amplitude; in the Beta range of frequency (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), meeting the threshold result in the change of state of the fan. Based on further analysis of the EEG signal in various frequency ranges, multiple such IOT devices can be controlled.…”

Exploring the Potential of Combining Smart Glasses and Consumer-grade EEG/EMG Headsets for Controlling IoT Appliances in the Smart Home

“…The same principle has been used to control a quadcopter [8]. In [9] and [10], the eMotiv headset is combined with an eye-tracker into a system for cursor manipulation and manipulation of a smart TV respectively. By combining a neuro headset with smart glasses, we allow users to quickly change control of one device to another, each time presenting the appropriate instructions in the near-to-eye display of the smart glass and translating the EEG/EMG signals to the correct device control command.…”

“…The EMG events are mapped onto commands for the IoT device identified through object recognition. To cope with the different protocols and interfaces of IoT devices, we leverage on the our Dynamic Adaptive Management of Networks and Devices (DYAMAND) middleware [9]. DYAMAND abstracts devicespecific syntax into service types that describe device functionality in more generic ways.…”