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  • 1.
    Atefi, Seyed Reza
    KTH-School of Technology and Health.
    Electrical Bioimpedance Cerebral Monitoring: From Hyopthesis and Simulation to First Experimental Evidence in Stroke Patients2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Stroke is amongthe leading causes of death worldwide and requires immediate care to prevent death or permanent disability. Unfortunately, the current stateof stroke diagnosis is limited to fixed neuroimaging facilities that do not allow rapid stroke diagnosis. Hence, a portable stroke-diagnosis device could assist in the pre-hospital triage of patients. Moreover, such a portable device could also be useful for bedside stroke monitoring of patients in the Neuro Intensive Care Unit (Neuro-ICU) to avoid unnecessary neuroimaging. Recent animal studies and numerical simulations have supported the idea of implementing Electrical Bioimpedance (EBI) in a portable device, allowing non-invasive assessment as a useful tool for the pre-hospital triage of stroke and Traumatic Brain Injury (TBI) patients. Unfortunately, these studies have not reported any results from human subjects in the acute phase of the stroke. The numerical simulations are also based on simple models that sometimes lack necessary details.

    Finite Element Method (FEM) simulations on a realistic numerical head model as well as experimental Bioimpedance Spectroscopy (BIS) measurements from human subjectsin the acute, subacute and chronic phasesof stroke were used to answer the following research questions: (i) Does stroke modify the electrical properties of brain tissue in a way that is detectable via EBI? (ii) Would it be possible to detect stroke via EBI as early as in the acute and sub-acute phase?(iii) Is EBI sensitive enough to monitor changes caused by stroke pathogenesis?

    Using FEM to simulate electrical current injection on the head and study the resulting distribution of electrical potential on the scalp, it was shown that Intra-Cranial Hemorrhage (ICH) affects the quasi-symmetric scalp potential distribution,creating larger left-right potential asymmetry when compared to the healthy head model. Proof-of-concept FEM simulations were also tested in a small cohort of 6ICH patients and 10 healthy controls, showing that the left-right potential difference in the patients is significantly (p<0.05) larger than in the controls. Using bioimpedance measurements in the acute,  subacute and chronic phasesof stroke and examining simple features, it was also shown that the head EBI measurements of patients suffering stroke are different from controls, enabling the discrimination of healthy controls and stroke patients at any stage of the stroke. The absolute change in test-retest resistance measurements of the control group (~5.33%) was also found to be significantly (p<0.05) smaller than the EBI measurements of patients obtained 24 hours and 72 hours after stroke onset (20.44%). These results suggested that scalp EBI is sensitive to stroke pathogenesis changesand thususeful for bedside monitoring in the Neuro-ICU. These results suggested that EBI is a potentially useful tool for stroke diagnosis and monitoring.

    Finally, the initial observations based on a small number of patients, addressing the proposed future work of this thesis, suggested that the average head resistance amplitude of hemorrhagic stroke patients is smaller than in healthy controls, while ischemic stroke patients show a larger resistance amplitude than the controls. Scalp potential asymmetry analysis of healthy, hemorrhagic and ischemic stroke subjects also suggests that these three groups can be separated. However, these results are based on a small number of patients and need to be validated using a larger cohort. Initial observations also showed that the resistance of the EBI measurements of controls is robust between test and retest measurements, showing no significant difference (less than 2% and p>0.05). Subject position during EBI recording (supine or sitting) did not seem to affect the resistance of the EBI measurements (p>0.05). However, age, sex and head size showed significant effects on the resistance measurements. These initial observations are encouraging for further research on EBI for cerebral monitoring and stroke diagnosis. However, at this stage, considering the uncertainties in stroke type differentiation, EBI cannot replace CT but has the potential to be used as a consultation tool.

  • 2.
    Atefi, Seyed Reza
    et al.
    Harvard Univsersity.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Kamalian, Shervin
    Rosenthal, Eric
    Lev, Michael
    Massachussets University Hospital.
    Bonmassar, Giorgio
    Harvard University.
    Intracranial haemorrhage alters scalp potential distributions in bioimpedance cerebral monitoring applications: preliminary results from FEM simulation on a realistic head model and human subjects2016In: Medical Physics, ISSN 0094-2405, Vol. 43, no 2, p. 675-686Article in journal (Refereed)
    Abstract [en]

    Purpose:

    Current diagnostic neuroimaging for detection of intracranial hemorrhage (ICH) is limited to fixed scanners requiring patient transport and extensive infrastructure support. ICH diagnosis would therefore benefit from a portable diagnostic technology, such as electrical bioimpedance (EBI). Through simulations and patient observation, the authors assessed the influence of unilateral ICH hematomas on quasisymmetric scalp potential distributions in order to establish the feasibility of EBI technology as a potential tool for early diagnosis.

    Methods:

    Finite element method(FEM) simulations and experimental left–right hemispheric scalp potential differences of healthy and damaged brains were compared with respect to the asymmetry caused by ICH lesions on quasisymmetric scalp potential distributions. In numerical simulations, this asymmetry was measured at 25 kHz and visualized on the scalp as the normalized potential difference between the healthy and ICH damaged models. Proof-of-concept simulations were extended in a pilot study of experimental scalp potential measurements recorded between 0 and 50 kHz with the authors’ custom-made bioimpedance spectrometer. Mean left–right scalp potential differences recorded from the frontal, central, and parietal brain regions of ten healthy control and six patients suffering from acute/subacute ICH were compared. The observed differences were measured at the 5% level of significance using the two-sample Welch t-test.

    Results:

    The 3D-anatomically accurate FEM simulations showed that the normalized scalp potential difference between the damaged and healthy brainmodels is zero everywhere on the head surface, except in the vicinity of the lesion, where it can vary up to 5%. The authors’ preliminary experimental results also confirmed that the left–right scalp potential difference in patients with ICH (e.g., 64 mV) is significantly larger than in healthy subjects (e.g., 20.8 mV; P < 0.05).

    Conclusions:

    Realistic, proof-of-concept simulations confirmed that ICH affects quasisymmetric scalp potential distributions. Pilot clinical observations with the authors’ custom-made bioimpedance spectrometer also showed higher left–right potential differences in the presence of ICH, similar to those of their simulations, that may help to distinguish healthy subjects from ICH patients. Although these pilot clinical observations are in agreement with the computer simulations, the small sample size of this study lacks statistical power to exclude the influence of other possible confounders such as age, sex, and electrode positioning. The agreement with previously published simulation-based and clinical results, however, suggests that EBI technology may be potentially useful for ICH detection.

  • 3.
    Atefi, Seyed Reza
    et al.
    Harvard University.
    Seoane, Fernando
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Thorlin, Thorleif
    salhgrenska Hospital.
    Lindecrantz, Kaj
    KTH-School of Technology and Health.
    Stroke Damage Detection Using Classification Trees on Electrical Bioimpedance Cerebral Spectroscopy Measurements2013In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, no 8, p. 10074-10086Article in journal (Refereed)
  • 4.
    Seoane, Fernando
    et al.
    University of Borås, Faculty of Textiles, Engineering and Business. University of Borås, Faculty of Caring Science, Work Life and Social Welfare. Karolinska Institutet.
    Atefi, Seyed Reza
    University of Borås, Faculty of Textiles, Engineering and Business. Harvard Univsersity.
    Electrical bioimpedance enabling prompt intervention in traumatic brain injury2017In: SPIE Micro-and Nanotechnology Sensors, Systems, and Applications IX, 2017Conference paper (Refereed)
  • 5.
    Seoane, Fernando
    et al.
    University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Atefi, Seyed Reza
    Harvard Univsersity.
    Tomner, Jens
    Karolinska Hospital.
    Kostulas, Konstantinos
    Karolinska Hospital.
    Lindecrantz, Kaj
    KTH-School of Technology and Health.
    Electrical Bioimpedance Spectroscopy on Acute Unilateral Stroke Patients: Initial Observations regarding Differences between Sides2015In: BioMed research international, Vol. 2015Article in journal (Refereed)
  • 6.
    Zhou, Bo
    et al.
    DFKI.
    Altamirano, Carlos Andres Velez
    DFKI.
    Zurian, Heber Cruz
    DFKI.
    Atefi, Seyed Reza
    University of Borås, Faculty of Textiles, Engineering and Business.
    Billing, Erik
    Högskolan i Skövde.
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. University of Borås, Faculty of Caring Science, Work Life and Social Welfare. KTH-School of Technology and Health.
    Lukowicz, Paul
    DFKI.
    Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction2017In: Sensors, Vol. 17, no 11Article in journal (Refereed)
  • 7.
    Zhou, Bo
    et al.
    DFKI.
    Cruz, Heber Zurian
    DFKI.
    Atefi, Seyed Reza
    University of Borås, Faculty of Textiles, Engineering and Business. Harvard University.
    Billing, Erik
    Högskolan i Skövde.
    Seoane, Fernando
    University of Borås, Faculty of Textiles, Engineering and Business. University of Borås, Faculty of Caring Science, Work Life and Social Welfare. Karolinska Institutet.
    Lukowicz, Paul
    DFKI.
    TouchMe: Full-textile Touch Sensitive Skin for Encouraging Human-Robot Interaction2017In: The robotic sense of touch: from sensing to understanding, workshop at the IEEE International Conference on Robotics and Automation (ICRA), May 29-June 3, Singapore, 2017Conference paper (Refereed)
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