Network modelling methods for FMRI.

Assistive social robots, a particular type of assistive robotics designed for social interaction with humans, could play an important role with respect to the health and psychological well-being of the elderly. Objectives Assistive social robots are believed to be useful in eldercare for two reasons, a functional one and an affective one. Such robots are developed to function as an interface for the elderly with digital technology, and to help increase the quality of life of the elderly by providing companionship, respectively. There is a growing attention for these devices in the literature. However, no comprehensive review has yet been performed to investigate the effectiveness of such robots in the care of the elderly. Therefore, we systematically reviewed and analyzed existing literature on the effects of assistive social robots in health care for the elderly. We focused in particular on the companion function. Data Sources A systematic search of MEDLINE, CINAHL, PsycINFO, The Cochrane Library databases, IEEE, ACM libraries and finally Google Scholar was performed for records through December 2007 to identify articles of all studies with actual subjects aimed to assess the effects of assistive social robots on the elderly. This search was completed with information derived from personal expertise, contacts and reports. Study Selection and Data Extraction Since no randomized controlled trials (RCT)’s have been found within this field of research, all studies reporting effects of assistive robotics in elderly populations were included. Information on study design, interventions, controls, and findings were extracted for each article. In medical journals only a few articles were found, whereas about 50 publications were found in literature on ICT and robotics. Data Synthesis The identified studies were all published after 2000 indicating the novelty of this area of research. Most of these publications contain the results of studies that report positive effects of assistive social robots on health and psychological well-being of elders. Solid evidence indicating that these effects can indeed be attributed to the actual assistive social robot, its behavior and its functionality is scarce. Conclusions There is some qualitative evidence as well as limited quantitative evidence of the positive effects of assistive social robots with respect to the elderly. The research designs, however, are not robust enough to establish this. Confounding variables often cannot be excluded. This is partly due to the chosen research designs, but also because it is unclear what research methodology is adequate to investigate such effects. Therefore, more work on methods is needed as well as robust, large-scale studies to establish the effects of these devices.

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Assistive social robots in elderly care: a review

The rapidly ageing population is placing increasing strain on healthcare services. Robots have been proposed as a way to assist people to stay healthy and safe in their own homes. However, despite the need for such assistive devices and the success of some healthcare robots, other robots have had a poor response. This article reviews the literature about human responses to healthcare robots and summarises the variables that have been found to influence responses. It may be possible to increase acceptance of healthcare robots by properly assessing the needs of the human user and then matching the robot’s role, appearance and behaviour to these needs. Because robots have limitations in their abilities, another way to increase acceptance may be to modify the expectations of users to better match robots’ abilities. More research needs to investigate potential users’ needs and expectations in specific situations and whether interventions to increase the match between robot and human can increase acceptance.

Acceptance of Healthcare Robots for the Older Population: Review and Future Directions

Scalp electric potentials (electroencephalogram; EEG) are contingent to the impressed current density unleashed by cortical pyramidal neurons undergoing post-synaptic processes. EEG neuroimaging consists of estimating the cortical current density from scalp recordings. We report a solution to this inverse problem that attains exact localization: exact low-resolution brain electromagnetic tomography (eLORETA). This non-invasive method yields high time-resolution intracranial signals that can be used for assessing functional dynamic connectivity in the brain, quantified by coherence and phase synchronization. However, these measures are non-physiologically high because of volume conduction and low spatial resolution. We present a new method to solve this problem by decomposing them into instantaneous and lagged components, with the lagged part having almost pure physiological origin.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2011.0081

Assessing interactions in the brain with exact low-resolution electromagnetic tomography

Diagnosis of Alzheimer's disease.

A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG.

We used the seal robot, Paro, for therapy of patients suffering from dementia at a cortical neuron clinic. The efficacy of the robot therapy was evaluated by DIMENSION, which detects patient's cortical neuron activity from a 21-channel EEG. The results from preliminary experiments show that robot therapy has a high potential to improve the condition of brain activity in patients suffering from dementia. It is concluded that Paro will be widely used and provide help to people with dementia.

Robot therapy for elders affected by dementia

Medical studies have shown that EEG of Alzheimer's disease (AD) patients is “slower” (i.e., contains more low-frequency power) and is less complex compared to age-matched healthy subjects. The relation between those two phenomena has not yet been studied, and they are often silently assumed to be independent. In this paper, it is shown that both phenomena are strongly related. Strong correlation between slowing and loss of complexity is observed in two independent EEG datasets: (1) EEG of predementia patients (a.k.a. Mild Cognitive Impairment; MCI) and control subjects; (2) EEG of mild AD patients and control subjects. The two data sets are from different patients, different hospitals and obtained through different recording systems. The paper also investigates the potential of EEG slowing and loss of EEG complexity as indicators of AD onset. In particular, relative power and complexity measures are used as features to classify the MCI and MiAD patients versus age-matched control subjects. When combined with two synchrony measures (Granger causality and stochastic event synchrony), classification rates of 83% (MCI) and 98% (MiAD) are obtained. By including the compression ratios as features, slightly better classification rates are obtained than with relative power and synchrony measures alone.

/pdf/slowing-and-loss-of-complexity-in-alzheimer-s-eeg-two-sides-2d2m3zi8x1.pdf

Slowing and Loss of Complexity in Alzheimer's EEG: Two Sides of the Same Coin?

http://brain.bio.msu.ru/papers/Cichocki_Shishkin_Musha_Leonowicz_Asada_Kurachi_2005_ClinNeurophys_BSS_Filt_AD_correctedProof.pdf

EEG filtering based on blind source separation (BSS) for early detection of Alzheimer's disease

Robot therapy for demented patients was conducted at a cranial nerve clinic. Two therapeutic seal robots, Paro, were introduced there. This paper describes the results of this experiment. DIMENSION (diagnosis method of neuronal dysfunction) was used to analyze recorded patient's EEG before and after 20 minutes of robot therapy. Questionnaire concerning impression of seal robots was also conducted. The results showed that their cortical neurons activity was improved by interaction with the seal robots, especially for patients who liked the robots.

Toshimitsu Musha

Papers

A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG.

Robot therapy for elders affected by dementia

Slowing and Loss of Complexity in Alzheimer's EEG: Two Sides of the Same Coin?

EEG filtering based on blind source separation (BSS) for early detection of Alzheimer's disease

Effects of robot therapy for demented patients evaluated by EEG