Mauro Marchetti1, Konstantinos Priftis2. 1. Department of General Psychology, University of Padova, via Venezia 8, 35131 Padova, Italy. Electronic address: mauro.marchetti@unipd.it. 2. Department of General Psychology, University of Padova, via Venezia 8, 35131 Padova, Italy; Laboratory of Neuropsychology, IRCCS San Camillo Hospital, via Alberoni 70, 30126 Lido-Venice, Italy. Electronic address: konstantinos.priftis@unipd.it.
Abstract
OBJECTIVE: Despite recent groundbreaking findings on the genetic causes of amyotrophic lateral sclerosis (ALS), and improvements on neuroimaging techniques for ALS diagnosis have been reported, the main clinical intervention in ALS remains palliative care. Brain-computer interfaces (BCIs) have been proposed as a channel of communication and control for ALS patients. The present metanalysis was performed to test the evidence of BCI effectiveness in ALS, and to investigate whether the promising aims emerged from the first studies have been reached. METHODS: Studies on ALS patients tested with BCIs, until June 2013, were searched in PubMed and PsychInfo. The random-effect approach was used to compute the pooled effectiveness of BCI in ALS. A meta-regression was performed to test whether there was a BCI performance improvement as a function of time. Finally, BCI effectiveness for complete paralyzed ALS patients was tested. Twenty-seven studies were eligible for metanalysis. RESULTS: The pooled classification accuracy (C.A.) of ALS patients with BCI was about 70%, but this estimation was affected by significant heterogeneity and inconsistency. C.A. did not significantly increase as a function of time. C.A. of completely paralyzed ALS patients with BCI did not differ from that obtained by chance. CONCLUSIONS: After 15 years of studies, it is as yet not possible to reliably establish the effectiveness of BCIs. SIGNIFICANCE: Methodological issues among the retrieved studies should be addressed and new well-powered studies should be conducted to confirm BCI effectiveness for ALS patients.
OBJECTIVE: Despite recent groundbreaking findings on the genetic causes of amyotrophic lateral sclerosis (ALS), and improvements on neuroimaging techniques for ALS diagnosis have been reported, the main clinical intervention in ALS remains palliative care. Brain-computer interfaces (BCIs) have been proposed as a channel of communication and control for ALSpatients. The present metanalysis was performed to test the evidence of BCI effectiveness in ALS, and to investigate whether the promising aims emerged from the first studies have been reached. METHODS: Studies on ALSpatients tested with BCIs, until June 2013, were searched in PubMed and PsychInfo. The random-effect approach was used to compute the pooled effectiveness of BCI in ALS. A meta-regression was performed to test whether there was a BCI performance improvement as a function of time. Finally, BCI effectiveness for complete paralyzed ALSpatients was tested. Twenty-seven studies were eligible for metanalysis. RESULTS: The pooled classification accuracy (C.A.) of ALSpatients with BCI was about 70%, but this estimation was affected by significant heterogeneity and inconsistency. C.A. did not significantly increase as a function of time. C.A. of completely paralyzed ALSpatients with BCI did not differ from that obtained by chance. CONCLUSIONS: After 15 years of studies, it is as yet not possible to reliably establish the effectiveness of BCIs. SIGNIFICANCE: Methodological issues among the retrieved studies should be addressed and new well-powered studies should be conducted to confirm BCI effectiveness for ALSpatients.
Authors: Tomislav Milekovic; Anish A Sarma; Daniel Bacher; John D Simeral; Jad Saab; Chethan Pandarinath; Brittany L Sorice; Christine Blabe; Erin M Oakley; Kathryn R Tringale; Emad Eskandar; Sydney S Cash; Jaimie M Henderson; Krishna V Shenoy; John P Donoghue; Leigh R Hochberg Journal: J Neurophysiol Date: 2018-04-25 Impact factor: 2.714
Authors: Laura Carelli; Federica Solca; Andrea Faini; Paolo Meriggi; Davide Sangalli; Pietro Cipresso; Giuseppe Riva; Nicola Ticozzi; Andrea Ciammola; Vincenzo Silani; Barbara Poletti Journal: Biomed Res Int Date: 2017-08-23 Impact factor: 3.411