Application of Fast Perturbational Complexity Index to the Diagnosis and Prognosis for Disorders of Consciousness

Objective: Diagnosis and prognosis of patients with disorders of consciousness (DOC) is a challenge for neuroscience and clinical practice. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is an effective tool to measure the level of consciousness. However, a scientif...

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Main Authors: Yong Wang (Author), Zikang Niu (Author), Xiaoyu Xia (Author), Yang Bai (Author), Zhenhu Liang (Author), Jianghong He (Author), Xiaoli Li (Author)
Format: Book
Published: IEEE, 2022-01-01T00:00:00Z.
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001 doaj_f5d34e05dfc14938b4c8d50adbe89db3
042 |a dc 
100 1 0 |a Yong Wang  |e author 
700 1 0 |a Zikang Niu  |e author 
700 1 0 |a Xiaoyu Xia  |e author 
700 1 0 |a Yang Bai  |e author 
700 1 0 |a Zhenhu Liang  |e author 
700 1 0 |a Jianghong He  |e author 
700 1 0 |a Xiaoli Li  |e author 
245 0 0 |a Application of Fast Perturbational Complexity Index to the Diagnosis and Prognosis for Disorders of Consciousness 
260 |b IEEE,   |c 2022-01-01T00:00:00Z. 
500 |a 1558-0210 
500 |a 10.1109/TNSRE.2022.3154772 
520 |a Objective: Diagnosis and prognosis of patients with disorders of consciousness (DOC) is a challenge for neuroscience and clinical practice. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is an effective tool to measure the level of consciousness. However, a scientific and accurate method to quantify TMS-evoked activity is still lacking. This study applied fast perturbational complexity index (PCIst) to the diagnosis and prognosis of DOC patients. Methods: TMS-EEG data of 30 normal healthy participants (NOR) and 181 DOC patients were collected. The PCIst was used to assess the time-space complexity of TMS-evoked potentials (TEP). We selected parameters of PCIst in terms of data length, data delay, sampling rate and frequency band. In addition, we collected Coma Recovery Scale–Revised (CRS-R) values for 114 DOC patients after one year. Finally, we trained the classification and regression model. Results: 1) PCIst shows the differences among NOR, minimally consciousness state (MCS) and unresponsive wakefulness syndrome (UWS) and has low computational cost. 2) Optimal parameters of data length and delay after TMS are 300 ms and 101–300 ms. Significant differences of PCIst at 5–8 Hz and 9–12 Hz bands are found among NOR, MCS and UWS groups. PCIst still works when TEP is down-sampled to 250 Hz. 3) PCIst at 9–12 Hz shows the highest performance in diagnosis and prognosis of DOC. Conclusions: This study confirms that PCIst can quantify the level of consciousness. PCIst is a potential measure for the diagnosis and prognosis of DOC patients. 
546 |a EN 
690 |a TMS-EEG 
690 |a PCIst 
690 |a DOC 
690 |a diagnosis 
690 |a prognosis 
690 |a Medical technology 
690 |a R855-855.5 
690 |a Therapeutics. Pharmacology 
690 |a RM1-950 
655 7 |a article  |2 local 
786 0 |n IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 509-518 (2022) 
787 0 |n https://ieeexplore.ieee.org/document/9721843/ 
787 0 |n https://doaj.org/toc/1558-0210 
856 4 1 |u https://doaj.org/article/f5d34e05dfc14938b4c8d50adbe89db3  |z Connect to this object online.