RAY ARTERY PULSE SIGNAL CHARACTERISTICS USING IN THE CANCER AND BENIGN LUNG DISEASES DIFFERENTIAL DIAGNOSTICS PROBLEM
A. Desova 1, A. A. Dorofeyuk 1, 2, A. M. Anokhin 1,
J. A. Dorofeyuk 1
1 V.A.Trapeznikov Institute of Control
Sciences, Russian Academy of Sciences, Profsoyuznaya 65, Moscow 117997, Russia
2 Federal Research Center "Informatics and Management", Russian Academy of Sciences,
Vavilova 44-2, Moscow 119333, Russia
The paper is received on June
Abstract. The paper presents the radial artery
pulse signal characteristics analysis results, as applied to the solution of
the tumor (malignant and benign) lungs diseases differential diagnosis problem.
Research conducted on the real pulse signals basis obtained during patients
clinical examinations at the radiology Department of the Sechenov’s Moscow
medical Academy. The research purpose was to evaluate the possibility of the
lung tumors diseases differential diagnosis reliability increasing at the
clinical and radiological examination stage by using additional information
extracted from the radial artery pulse signal characteristics. It is known that
for clinical - radiological examination (without histological studies) the accuracy
of differential diagnosis between central lung cancer and limited pulmonary
fibrosis, as well as between peripheral lung cancer and tuberculoma is not high
enough, which requires the use of additional examination methods. Informative
signs were formed on the basis of values of the oscillatory component
describing the amplitude and time base variability of the pulse signal basic
period parameters, their mutual relations, and also a number of their
statistical characteristics. The features informative value evaluation and the
decision rule construction for investigated diseases differential diagnosis was
carried out using pattern recognition algorithms. The peripheral pulse signal
was measured on the radial artery of the patient's right hand using an optoelectronic
pulse signal sensor. The analyzed dataset classification (90 vectors on
"learning" and 50 vectors on the "exam") quality
recognition amounted to 89.5% of correct decisions for first class (malignant
diseases) and 78% for second class (benign diseases). As a classification
criterion the clinical diagnoses were used, in some cases confirmed by the
results of histological studies. The diagnostic consider method does not
require instrumental intervention, the use of expensive reagents, has no contraindications
and excludes the radiation loads. The method is relatively fast, not traumatic,
and allows simple and efficient differential diagnosis, regardless of the
location of the pathological formation and its size. The obtained results
indicate the diagnostic efficiency of the radial artery pulse signal rhythmic
structure using during clinical and pre-hospital examinations of pulmonological
patients. The method can be used as a population screening test in order to
identify a predisposition to malignant pathology.
Key words: Pulse signal, respiratory wave, pulse
rate, rhythm structure, diagnostics, informative sign.
1. Selyuzhitskiy I.V. Opukholevyye markery v diagnostike i monitoringe zlokachestvennykh novobrazovaniy v usloviyakh mnogoprofil'nogo lechebnogo uchrezhdeniya. Avtoref. dis. na soisk.
uch. step. dok. med. nauk. – Moscow, 1995. (In Russian)
2. Kutushov M.V. Rak – mify i real'nost': Priroda raka. Rannyaya i
sverkhrannyaya diagnostika. – Moscow, V. Sekachev Publ., 2011. 104 p. (In
3. Bayevskiy R.M., Ivanov G.G., Chireykin L.V. i dr. Analiz variabel'nosti
serdechnogo ritma pri ispol'zovanii razlichnykh elektrokardiologicheskikh
sistem. Metodicheskiye rekomendatsii. Ural'skiy kardiologicheskiy zhurnal –
Ural Cardiology Journal, 2002. ¹ 1. pp. 22-39. (In Russian)
4. Sorokin O.V., Subotyalov M.A. APK «VedaPul's» method of computer pulse diagnostics
on the base of traditional Aurved medicine. Aktual'nyye voprosy sanatornogo
lecheniya i meditsinskoy reabilitatsii: sbornik statey mezhregional'noy
nauchno-prakticheskoy konferentsii s mezhdunarodnym uchastiyem. Novosibirsk,
Sibmedizdat, NGMU Publ. 2013. pp. 156-160. (In Russian)
5. Rinchinov O.S. Radiofizicheskiye issledovaniya pul'sovykh signalov.
Dissertatsiya na soiskaniye uchonoy stepeni kandidata fiziko-matematicheskikh
nauk. Ulan-Ude, Otdel fizicheskikh problem Buryatskogo nauchnogo tsentra SO
RAN. 2000. 143 p. (In Russian)
6. Boronoyev V.V. Pul'sovaya diagnostika zabolevaniy v tibetskoy meditsine:
fizicheskiye i tekhnicheskiye aspekty. Ulan-Ude. BNTS SO RAN Publ. 2005. 320 p.
7. Fleyshman A.N., Martynov I.D., Petrovskiy S.A., Korablina T.V.
Ortostaticheskaya takhikardiya: diagnosticheskoye i prognosticheskoye
znacheniye very low frequency variabel'nosti ritma serdtsa. Byulleten'
sibirskoy meditsiny – Siberia Medicine Bulletin, 2014. vol 13. N 4. pp.
136-148. (In Russian)
8. V.A. Snezhitskiy. Metodologicheskiye aspekty analiza variabel'nosti
serdechnogo ritma v klinicheskoy praktike. Meditsinskiye novosti – Medical News. 2004. N 9. p. 37-43. (In Russian)
Fan, Gong Zhang, Simon Liao. Pulse Wave Analysis. Advanced Biomedical Engineering, Dr.
Gaetano Gargiulo (Ed.), 2011, pp. 21-40. InTech, 280 p.
10. Desova A.A., Dorofeyuk A.A., Maksimov D.YU. Portativnaya komp'yuternaya
sistema registratsii pul'sovykh signalov. Datchiki i sistemy – Sensors and
Systems. 2008. N 4. pp. 29-32. . (In Russian)
11. Desova A.A., Guchuk V.V. and Dorofeyuk A.A. A new approach to pulse signal
rhythmic structure analysis. Int. J. Biomedical Engineering and Technology.
2014. vol. 14. ¹. 2. pp.148-158.
12. Vapnik V.N. (red.) Algoritmy i programmy vosstanovleniya zavisimostey.
[Algorithms and programs for recovering dependences]. Moscow, Fizmatlit Publ. 1984. 816 p. (In Russian)
A. Desova, A. A. Dorofeyuk, A. M. Anokhin,
J. A. Dorofeyuk.
Ray artery pulse signal
characteristics using in the cancer and benign lung diseases differential
Zhurnal Radioelektroniki - Journal of Radio Electronics,
7. Available at http://jre.cplire.ru/jre/jul17/9/text.pdf.