BCI-Ageing: BCI tools for promoting active ageing
Brain Computer Interface for cognitive training and domotic assistance against the effects of ageing.

Results

The BCI-Ageing project proposed BCI tools for promoting active ageing. More specifically, we developed two BCI-based applications:

  1. BCI tool for cognitive training against the effects of ageing
  2. BCI tool for domotic assistance at home


BCI tool for cognitive training

A BCI tool for cognitive training was developed by means of a motor imagery (MI)-based BCI. The proposed tool allows users to perform neurofeedback training (NFT) and working memory cognitive training (WMCT) tasks. More specifically, five different NFT tasks and one CT task were implemented.

  • NFT Task 1. A closed door is shown during the pre-feedback phase. The user has to imagine repeatedly right hand movements to open the door during the feedback phase. If the image shown is a closed window, then the user has to imagine repeatedly left hand movements to open the window.
  • NFT Task 2. A house, a wardrobe or a fridge is shown on the right or the left side of the screen. During the feedback phase, a silhouette of a man, a pair of trousers or a fish appears on the centre of the screen. The user has to imagine repeatedly right or left hand movements in order to move the corresponding cursor towards the side of the screen where the target is shown.
  • NFT Task 3. A wardrobe and a fridge are shown one on each side of the screen. In the feedback phase, a cursor (a pair of trousers, a shirt, a fish or a steak) appears on the centre of the screen. The user has to imagine repeatedly right or left hand movements in order to move the cursor towards the right target (the wardrobe for clothes and the fridge for food).
  • NFT Task 4. In this task a cursor represented by a man walking through a road is shown. The user has to move the walking man to the left or to the right in order to avoid the incoming obstacles. The application has two levels of increasing difficulty.
  • NFT Task 5. This task presents three different levels. In the first level, the application shows a figure on the left side of the screen and another different figure (same colour) on the right side. Then, both figures disappear and the task shows again two figures: one of the two figures showed previously and a different one. The user has to imagine repeatedly right or left hand movements in order to move the cursor towards the figure that appeared during the pre-feedback phase. In the second level, figures are presented to the user showing different colours. In the third level, the application shows faces with different expressions.
  • WMCT tasks. There are 5 different levels and users have to memorize figures. Two images are presented firstly, which are called “stimulus”. The user has to memorize them. Two new images are presented after a short waiting time, which are called “response”: one of the two figures showed before or another different one. The user has to press the spacebar if the response figure is different or another key if it has already been showed in the last stimulus.

Assessment of the NFT-BCI tool

Sixty three people, recruited by the National Reference Centre on Disability and Dependence (CRE-DyD) from San Andrés del Rabanedo (León, Spain), participated in the assessment of the NFT-BCI tool. All participants were older than 60 years, healthy and without any neuropsychological disorder. Thirty one (13 male, 18 female, mean age = 62.3, range = 63-81) received neurofeedback training (experimental group), while the remaining thirty two (9 male, 23 female, mean age = 68.0, range = 61-80) did not (control group).

Subjects from both groups (experimental and control groups) performed the Luria Adult Neuropsychological Diagnosis (AND) test. The Luria test includes nine sub-tests distributed in five different areas: visuospatial (visual perception and spatial orientation), oral language (receptive speech and expressive speech), memory (immediate memory and logical memory), intelligence (thematic draws and conceptual activity) and attention (attentional control). Participants from the experimental group performed 10 cognitive training sessions with the proposed BCI-based application: 5 NFT sessions alternated with 5 WMCT sessions. After performing cognitive training sessions, we found significant differences between both groups (experimental vs. control) for several functions: visual perception, expressive speech, immediate memory, thematic drawings and conceptual activity. Furthermore, scores for tests of these functions were significantly higher for subjects in the experimental group after carrying out the CT programme compared to controls.

BCI tool for assistance of severely impaired people at home

A BCI tool for assisting dependent elderly people at home was developed by means of a P300-based BCI. The proposed tool allows users to manage 8 electronic devices usually present at home: TV, DVD player, Hi-Fi system, multimedia hard drive, lights, heater, fan and phone. Thus, the main comfort, communication and entertainment needs are fulfilled. The assistive BCI-based application works as follows:

  1. The application shows images of all home appliances that can be managed or all control commands of a specific device.
  2. The application detects P300 potentials in the user’s EEG in order to infer which device/command the user wants to manage.
  3. The application sends the desired infrared (IR) command to the device in order to perform the user’s intent. The emitted IR command is the same as if the subject uses the remote control of the device. Thus, all commands from all the remote controls managed by the assistive tool have to be previously stored in the PC were the BCI-based application runs. To do that, IR emitter and control software by RedRat (RedRat Ltd., Cambridge, UK) are used.

Assessment of the assistive BCI tool

Thirty people, recruited through the National Reference Centre on Disability and Dependence (CRE-DyD) from San Andrés del Rabanedo (León, Spain), participated in the assessment of the P300-based tool. All subjects (19 males, 11 females; mean age = 48.7 years, range = 26-68) performed three sessions (a first one for calibration and two evaluation sessions) and one neuropsychological evaluation by means of the Luria test. They were all potential BCI end-users since they presented motor disabilities. Moreover, they were BCI-naive (without any BCI previous experience).

Our results showed that 23 out of the 30 participants were able to properly manage the proposed tool with accuracy higher than 80%. Nineteen out of them even achieved accuracy above 95%. Moreover, the users’ performance was analysed in order to explore its relation to the Luria-AND scores achieved for each participant. Statistical significant differences were not found between the accuracy or information transfer rate (ITR) reached by the patients and the Luria scores for specific cognitive functions. Therefore, our results suggest that P300-based BCIs could be really suitable to assist severely impaired people at their own home.

If you want to obtain additional information, you can download the following document, which shows in detail the results of the BCI-Ageing project.