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“School of Nano-Sciences”

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Paper   IPM / Nano-Sciences / 13013
School of Nano Science
  Title:   Quantifying Memory in Complex Physiological Time- Series
  Author(s): 
1 . Amir Hossein Shirazi
2 . Mohammad Raoufy
3 . Haleh Ebadi
4 . Michele De Rui
5 . Sami Schiff
6 . Roham Mazloom
7 . Sohrab Hajizadeh
8 . Shahriar Gharibzadeh
9 . Ahmad Dehpour
10 . Pierre Amodio
11 . Gholam Reza Jafari
12 . Sara Montagnese
13 . Ali Mani
  Status:   Published
  Journal: Plos One
  No.:  9
  Vol.:  8
  Year:  2013
  Pages:   1-8
  Editor:  Martin Gerbert Frasch
  Supported by:  IPM
  Abstract:
In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are "forgotten" quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

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