@article{fdi:010087328,
  title = {{E}xploring time series retrieved from cardiac implantable devices for optimizing patient follow-up},
  author = {{G}ueguin, {M}. and {R}oux, {E}mmanuel and {H}ernandes, {A}.{I}. and {P}oree, {F}. and {M}abo, {P}. and {G}raindorge, {L}. and {C}arrault, {G}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}urrent cardiac implantable devices ({ID}s) are equipped with a set of sensors that can provide useful information to improve patient follow-up and prevent health deterioration in the postoperative period. {I}n this paper, data obtained from an {ID} with two such sensors (a transthoracic impedance sensor and an accelerometer) are analyzed in order to evaluate their potential application for the follow-up of patients treated with a cardiac resynchronization therapy ({CRT}). {A} methodology combining spatiotemporal fuzzy coding and multiple correspondence analysis ({MCA}) is applied in order to: 1) reduce the dimensionality of the data and provide new synthetic indexes based on the 'factorial axes' obtained from {MCA}; 2) interpret these factorial axes in physiological terms; and 3) analyze the evolution of the patient's status by projecting the acquired data into the plane formed by the first two factorial axes named 'factorial plane'.{I}n order to classify the different evolution patterns, a new similarity measure is proposed and validated on the simulated datasets, and then, used to cluster observed data from 41 {CRT} patients. {T}he obtained clusters are compared with the annotations on each patient's medical record. {T}wo areas on the factorial plane are identified, one being correlated with a health degradation of patients and the other with a stable clinical state},
  keywords = {},
  booktitle = {},
  journal = {{IEEE} {T}ransactions on {B}iomedical {E}ngineering},
  volume = {55},
  numero = {10},
  pages = {2343--2352},
  ISSN = {0018-9294},
  year = {2008},
  DOI = {10.1109/{TBME}.2008.926673 },
  URL = {https://www.documentation.ird.fr/hor/fdi:010087328},
}