Towards an Accessible Use of a Brain-Computer Interfaces-Based Home Care System through a Smartphone

Abstract

This study proposes a home care system (HCS) based on a brain-computer interface (BCI) with a smartphone. The HCS provides daily help to motor-disabled people when a caregiver is not present. The aim of the study is two-fold: (1) to develop a BCI-based home care system to help end-users control their household appliances, and (2) to assess whether the architecture of the HCS is easy for motor-disabled people to use. A motion-strip is used to evoke event-related potentials (ERPs) in the brain of the user, and the system immediately processes these potentials to decode the user’s intentions. The system, then, translates these intentions into application commands and sends them via Bluetooth to the user’s smartphone to make an emergency call or to execute the corresponding app to emit an infrared (IR) signal to control a household appliance. Fifteen healthy and seven motor-disabled subjects (including the one with ALS) participated in the experiment. The average online accuracy was 81.8% and 78.1%, respectively. Using component N2P3 to discriminate targets from nontargets can increase the efficiency of the system. Results showed that the system allows end-users to use smartphone apps as long as they are using their brain waves. More important, only one electrode O1 is required to measure EEG signals, giving the system good practical usability. The HCS can, thus, improve the autonomy and self-reliance of its end-users.

Informal Caregiving in Amyotrophic Lateral Sclerosis (ALS): A High Caregiver Burden and Drastic Consequences on Caregivers’ Lives

“…Although, there is a lot of knowledge on caregiving in ALS and the needs of CGs [20], established institutional structures to support informal caregivers and the families of the affected patients are still missing, as far as we know, in Germany and other countries. There are investigations of different strategies to relieve the families' caregiver burden in neurological disorders, like paid CGs instead of informal CGs and mobile gerontopsychiatric counseling services in dementia [21,22], psychological support for partners of patients with ALS [23], psychoeducational intervention in people with Parkinson's disease and their informal caregivers [24], or even new technologies like the use of a brain-computer interfaces-based home care system [25]. Nevertheless, none of these showed a widespread success, so as not to be implemented into standard care yet; therefore, unmet needs commonly remain unchanged.…”

Brain–Computer Interface (BCI) Control of a Virtual Assistant in a Smartphone to Manage Messaging Applications

“…Commercial or everyday devices are not adapted to be controlled directly through a BCI system. Three of the mentioned papers implemented an interaction with a smartphone [ 20 , 22 , 25 ], and the three used Bluetooth to send control commands from the BCI to the smartphone. In [ 20 , 25 ] authors connected an Arduino Bluetooth module to a computer to send the commands and installed a custom-made application in the smartphone to receive and interpret these commands.…”

“…Three of the mentioned papers implemented an interaction with a smartphone [ 20 , 22 , 25 ], and the three used Bluetooth to send control commands from the BCI to the smartphone. In [ 20 , 25 ] authors connected an Arduino Bluetooth module to a computer to send the commands and installed a custom-made application in the smartphone to receive and interpret these commands. In the case of [ 22 ], a computer directly sent the control commands via Bluetooth to the smartphone, but unfortunately, the authors did not provide the details on how the smartphone received and interpreted these commands (they only mentioned “The selected commands are sent in real-time to the final Android device via Bluetooth, which interprets them and provides visual feedback to the user”); we guess that they also used an application running in the smartphone to receive and interpret the control commands.…”

Design-development of an at-home modular brain–computer interface (BCI) platform in a case study of cervical spinal cord injury

“…However, other implementations have used smartphones for signal processing—using the phone as the sole processing unit for the system [ 55 – 58 ]—as opposed to using an on-board minicomputer. Others have used smartphones to drive communication with home appliances [ 35 , 36 ]. Here, the use of NativeScript limited the development of the phone application to Bluetooth Low Energy protocols, which limits our system’s ability for high bandwidth data streaming that Bluetooth classic radio frequency communication (RFCOMM) could otherwise achieve for raw signal transmission.…”

“…One method for increasing portability, is using smaller computational equipment that has become more readily available in personal tablets, phones, and minicomputers. Several previous studies have used portable devices such as tablets and phones for command [ 35 ] and signal processing [ 55 , 57 , 58 ], subject interaction [ 38 ], and as the end effector itself [ 56 ]. For our design, we used a minicomputer and the subject’s smartphone, which allowed us to give the subject control of the BCI while ensuring that the BCI software could continue running independently of the phone.…”