History and Technical Foundations of Z Score EEG Biofeedback

2015 ◽  
pp. 1-21 ◽  
Author(s):  
Robert W. Thatcher ◽  
Carl J. Biver ◽  
Duane M. North
Keyword(s):  
Eeg Biofeedback ◽  
Z Score

scholarly journals Advances in Electrical Neuroimaging, Brain Networks and Neurofeedback Protocols

2020 ◽  
Author(s):  
Robert W. Thatcher ◽  
Carl J. Biver ◽  
Ernesto Palermero Soler ◽  
Joel Lubar ◽  
J. Lucas Koberda
Keyword(s):  
Human Brain ◽  
Real Time ◽  
Brain Mapping ◽  
Brain Networks ◽  
Three Dimensional ◽  
Brain Network ◽  
Eeg Biofeedback ◽  
Reference Database ◽  
Z Score ◽  
Electrical Neuroimaging

Human EEG biofeedback (neurofeedback) started in the 1940s using 1 EEG recording channel, then to 4 channels in the 1990s. New advancements in electrical neuroimaging expanded EEG biofeedback to 19 channels using Low Resolution Electromagnetic Tomography (LORETA) three-dimensional current sources of the EEG. In 2004–2006 the concept of a “real-time” comparison of the EEG to a healthy reference database was developed and tested using surface EEG z-score neurofeedback based on a statistical bell curve called “real-time” z-scores. The “real-time” or “live” normative reference database comparison was developed to help reduce the uncertainty of what threshold to select to activate a feedback signal and to unify all EEG measures to a single value, i.e., the distance from the mean of an age matched reference sample. In 2009 LORETA z-score neurofeedback further increased the specificity by targeting brain network hubs referred to as Brodmann areas. A symptom check list program to help link symptoms to dysregulation of brain networks based on fMRI and PET and neurology was created in 2009. The symptom checklist and NIH based networks linking symptoms to brain networks grew out of the human brain mapping program starting in 1990 which is continuing today. A goal is to increase specificity of EEG biofeedback by targeting brain network hubs and connections between hubs likely linked to the patient’s symptoms. New advancements in electrical neuroimaging introduced in 2017 provide increased resolution of three-dimensional source localization with 12,700 voxels using swLORETA with the capacity to conduct cerebellar neurofeedback and neurofeedback of subcortical brain hubs such as the thalamus, amygdala and habenula. Future applications of swLORETA z-score neurofeedback represents another example of the transfer of knowledge gained by the human brain mapping initiatives to further aid in helping people with cognition problems as well as balance problems and parkinsonism. A brief review of the past, present and future predictions of z-score neurofeedback are discussed with special emphasis on new developments that point toward a bright and enlightened future in the field of EEG biofeedback.

Z-Score EEG Biofeedback: Past, Present, and Future

Biofeedback ◽  
2019 ◽  
Vol 47 (4) ◽  
pp. 89-103
Author(s):  
Robert W. Thatcher ◽  
Joel F. Lubar ◽  
J. Lucas Koberda
Keyword(s):  
Human Brain ◽  
Real Time ◽  
Brain Mapping ◽  
Three Dimensional ◽  
Brain Network ◽  
Eeg Biofeedback ◽  
Reference Database ◽  
Symptom Checklist ◽  
Z Score ◽  
Human Brain Mapping

Human electroencephalogram (EEG) biofeedback (neurofeedback) started in the 1940s using one EEG recording channel, then four channels in the 1990s, and in 2004, expanded to 19 channels using Low Resolution Electromagnetic Tomography (LORETA) of the microampere three-dimensional current sources of the EEG. In 2004–2006 the concept of a real-time comparison of the EEG to a healthy reference database was developed and tested using surface EEG z score neurofeedback based on a statistical bell curve called real-time z scores. The real-time or live normative reference database comparison was developed to help reduce the uncertainty of what threshold to select to activate a feedback signal and to unify all EEG measures to a single value (i.e., the distance from the mean of an age-matched reference sample). In 2009 LORETA z score neurofeedback further increased specificity by targeting brain network hubs referred to as Brodmann areas. A symptom checklist program to help link symptoms to dysregulation of brain networks based on fMRI and positron emission tomography (PET) and neurology was created in 2009. The symptom checklist and National Institutes of Health–based networks linking symptoms to brain networks grew out of the human brain mapping program started in 1990 that continues today. A goal is to increase specificity of EEG biofeedback by targeting brain network hubs and connections between hubs likely linked to the patient's symptoms. Developments first introduced in 2017 provide increased resolution of three-dimensional source localization with 12,700 voxels using swLORETA with the capacity to conduct cerebellar neurofeedback and neurofeedback of subcortical brain hubs such as the thalamus, amygdala, and habenula. Future applications of swLORETA z score neurofeedback represent another example of the transfer of knowledge gained by the human brain mapping initiatives to further aid in helping people with cognition problems as well as balance problems and parkinsonism. A brief review of the past, present, and future predictions of z score neurofeedback are discussed with special emphasis on new developments that point toward a bright and enlightened future in the field of EEG biofeedback.

scholarly journals EEG Biofeedback Case Studies Using Live Z-Score Training and a Normative Database

2010 ◽  
Vol 14 (1) ◽  
pp. 22-46 ◽  
Author(s):  
Thomas F. Collura ◽  
Joseph Guan ◽  
Jeffrey Tarrant ◽  
John Bailey ◽  
Fred Starr
Keyword(s):  
Case Studies ◽  
Eeg Biofeedback ◽  
Z Score ◽  
Normative Database

ANALISA KESEHATAN KEUANGAN PERUSAHAAN UNTUK MEMPREDIKSI KEBANGKRUTAN PERUSAHAAN DENGAN MENGGUNAKAN METODE ALTMAN (STUDI KASUS PADA PERUSAHAAN MANUFAKTUR SEKTOR KOMPONEN OTOMOTIF YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2011 – 2015)

2019 ◽  
Vol 13 (2) ◽  
pp. 55
Author(s):  
Indar Khaerunnisa ◽  
Edy Cahyadi
Keyword(s):  
Motor Vehicle ◽  
Stock Exchange ◽  
Secondary Data ◽  
Z Score ◽  
Financial Ratio ◽  
Average Value ◽  
Automotive Components ◽  
Grey Area ◽  
Financial Ratio Analysis ◽  
Year 2013

The Indonesian government has set the motor vehicle industry as one of the priority industries of the national interest, economic growth, and increased productivity. In order for the survival of a company is maintained, then the management should be able to maintain or even more spur increased performance. Various analyzes were developed to predict the beginning of the bankruptcy of the company. One analysis is widely used today is the analysis of Altman Z-Score, which this analysis refers to the financial ratios of the company. The purpose of this study was to analyze the bankruptcy of the automotive components companies that go public in Indonesia Stock Exchange year period 2011–2015. This study used a sample of four companies from the automotive components sector. Source of data is done by using secondary data. The data is processed by the method of the Z-score formula Z = 1,2X1 + 1,4X2 + 3,3X3 + 0,6X4 + 0,999X5. With the description of Z < 1,8 the company categorized into unhealthy/will be bankrupt, the value Z 1,8 < 2,99 the company is considered to be in the uncertain/grey area and the value of Z > 2,99 then the company is in a very healthy. In general, the results of these studies indicate that the four automtive components companies namely PT Astra Otoparts year 2011 value of Z = 14,67 year 2012 value of Z = 10,88 year 2013 value of Z = 13,90 year 2014 value of Z = 10,54 year 2015 value of Z = 4,94, PT Gajah Tunggal year 2011 value of Z = 5,72 year 2012 value of Z = 4,75 year 2013 value of Z = 3,10 year 2014 value of Z = 2,79 year 2015 value of Z = 1,58 and the average value of 2011-2015 periode Z = 3,59, PT Goodyear Indonesia year 2011 value of Z = 2,07 year 2012 value of Z = 2,44 year 2013 value of Z = 2,57 year 2014 value of Z = 2,02 year 2015 value of Z = 2,76, PT Indomobil Sukses Internasional year 2011 value of Z = 6,19 year 2012 value of Z = 3,99 year 2013 value of Z = 3,17 year 2014 value of Z = 2,59 year 2015 value of Z = 1,74. The average value 2011-2015 period showed 3 companies are in very healthy state and 1 company is in the uncertain/grey area. Keywords: Financial Ratio Analysis, Analysis of bankruptcy, Altman Z-Score Analysis, Automotive Components Company, Go Public.

Двухжелудочковая коррекция врожденных пороков сердца у пациентов с гипоплазией структур левых отделов сердца: морфометрические и гемодинамические критерии

2020 ◽  
Author(s):  
L.A. Bokeriia ◽  
S.V. Kalashnikov ◽  
I.E. Nefedova
Keyword(s):  
Z Score

Цель.Определить морфометрические и гемодинамические критерии возможности выполнения двухжелудочковой коррекции у новорожденных и детей первого года жизни с врожденными пороками сердца (ВПС), сопровождающимися гипоплазией структур левого сердца. Материал и методы. В период с 2003 по 2016 г. в НМИЦССХ им. А.Н. Бакулева было пролечено 56 пациентов первого года жизни со сложными ВПС, сочетающимися с гипоплазией структур левых отделов сердца. В зависимости от морфометрических и морфофункциональных данных пациенты были разделены на две группы: 1-я группа одномоментной двухжелудочковой коррекции (n29), 2-я этапной двухжелудочковой коррекции (n27). Средний возраст на момент первичного поступления составил 35,955,4 дня (от 1 дня до 7,5 мес), масса тела на момент первичного обращения в общей группе 3,81,1 (2,177,6) кг, площадь поверхности тела 0,240,047 (0,160,36) м2. Z-score митрального клапана (МК) на момент первичного вмешательства в 1-й группе составил 2,770,70 (0,84...4,14), Z-score аортального клапана (АК) составил 2,890,85 (0,58...4,5), индексированный конечный диастолический объем левого желудочка (иКДО ЛЖ) 21,33,99 (1635). Z-score МК на момент первичного вмешательства во 2-й группе составил 3,540,74 (1,55...4,70), Z-score АК составил 4,351,11 (2,63...7,04), иКДО ЛЖ 17,663,06 (1222). Всем пациентам были выполнены различные оперативные вмешательства, направленные на создание двухжелудочковой гемодинамики. Пациенты, умершие в раннем послеоперационном периоде по причине сердечной недостаточности, составили группу контроля (8 пациентов). Результаты. Если размеры (Z-score) кольца МК более 4,5, кольца АК более 6, выводного отдела ЛЖ более 6, восходящей аорты более 4, дуги аорты более 4, иКДО ЛЖ (мл/м2) более 15, отношение длины ЛЖ/ПЖ по продольной оси 0,8 и более, то оптимальным является выполнение одножелудочковой коррекции. Были определены гемодинамические и морфометрические показания к одномоментной и этапной двухжелудочковой коррекции. Выводы. У пациентов со сложными ВПС, сочетающимися с гипоплазией структур левых отделов сердца и обструкцией кровотока через левые отделы, успешная двухжелудочковая коррекция возможна не менее чем в 85 случаев.

ANALISIS PREDIKSI POTENSI KEBANGKRUTAN PADA PT BANK MUAMALAT INDONESIA Tbk PERIODE 2012-2016 DENGAN MENGGUNAKAN METODE ALTMAN MODIFIKASI

2017 ◽  
Vol 5 (2) ◽  
pp. 287-324
Author(s):  
Dewi Laela Hilyatin
Keyword(s):  
Financial Performance ◽  
Financial Structure ◽  
Financial Statements ◽  
Financial Ratios ◽  
Z Score ◽  
Altman Analysis ◽  
Gray Area ◽  
Modification Method ◽  
A Company

Abstract Bankruptcy is a very essential issue that every company should be aware of. Bankruptcy of a company can be minimized by advanced prediction; such as analyzing the financial statements. This study discusses the financial performance of PT Bank Muamalat Indonesia Tbk, which indicates that there is a degression in some number of financial ratios, the closing of offices and firing of employees in 2012-2016, causing he fact that BMI must pay attention and improve its financial performance and anticipate the existence of a bankruptcy in the company. Based on Altman analysis modification for financial performance of PT Bank Muamalat Indonesia Tbk in 2012-2016, it found Z-Score value of 0,825, 0,659, 1,243, 0,982 and 0,892. Based on Z-Score criteria, PT Bank Muamalat Indonesia Tbk is predicted to experience problems in management and financial structure and also in potentially bankruptcy due to Z-Score value <1,1 while the highest Z-Score value is in 2014, which shows the value of Z-Score>1,1 and <2,6, which means the company is in the gray area, meaning the company’s category is not said to be bankrupt and also not healthy. Keywords: Bankruptcy, Altman Modification Method

Financial Statement Ratio Analysis to Predict Bankruptcy nn Company Registered in BEI - Jakarta (Altman Z-Score Method and Zmijewski)

2020 ◽  
Vol 3 (3) ◽  
pp. 122
Author(s):  
Andi Silvan
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Good Condition ◽  
Financial Statement ◽  
Depth Information ◽  
Z Score ◽  
Industrial Manufacturing ◽  
Financial Difficulties ◽  
A Value ◽  
Score Method

AbstractThis study takes the topic of predicting corporate bankruptcies. This research dqlam use traditional methods Altman Z-Score and Zmijewski. The purpose of this study was to obtain in-depth information about predicting bankruptcy of companies that are not necessarily directly to bankruptcy, but there is financial distress.Based on the results of research conducted on the four (4) non industrial manufacturing company listed on the Indonesia Stock Exchange (BEI). Obtaining the value z-score represents the average company are in good condition, which means no financial distress. Acquisition value of x-score has a value of less than 0 (zero) which means that the company is in good condition and is predicted not experiencing financial difficulties. This study led to the conclusion that the Altman Z-Score and Zmijewski method can be used to predict corporate bankruptcy. Keywords: Financial Ratios, Bankruptcy, Company.

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