Understanding the Effect of Cannabis Abuse on the ANS and Cardiac Physiology of the Indian Women Paddy-field Workers Using RR Interval and ECG Signal Analyses Abstract— The current study was an attempt to understand the effect of cannabis (bhang) abuse on the autonomic nervous system (ANS) and the cardiac physiology of the Indian women working in paddy fields. Electrocardiogram (ECG) signals were collected from twenty-five volunteers, and RR intervals (RRIs) were extracted. Recurrence analysis of RRI series suggested a reduction in the isometric recurrence and heart rate stability in women abusing cannabis. The effect on ANS was estimated using non-invasive heart rate variability (HRV) analysis. The results suggested a decline in the sympathovagal balance and the parasympathetic activity following regular cannabis abuse. The effect of cannabis abuse on the heart was examined using time- domain and wavelet-based analysis of ECG signals. The results suggested an alteration in the cardiac electrophysiology due to the cannabis abuse. The alterations in the ANS and heart activity were also evident from the adequately efficient (≥ 85%) artificial neural network (ANN)-based classification of the HRV and the ECG signal features, respectively. These effects of cannabis abuse can be added to those already reported and will tender additional evidence for counseling women to stop abusing cannabis. Keywords— Cannabis; Women; RR Interval; Recurrence; Heart Rate Variability I. INTRODUCTION Cannabis-based products (e.g. marijuana, hashish and bhang) have been abused for recreational purposes worldwide due to their euphoric effects. It is obtained from a flowering plant, categorized under the family of Cannabaceae. The plant is commonly found in Central Asia and the Indian subcontinent [1]. It has been well-documented more than half- a-century ago that cannabis is associated with a low level of toxicity [2]. Many researchers have reported the adverse effects of cannabis abuse on health, like anxiety, dysphoria, cognitive impairment, psychomotor impairment, chronic bronchitis, increased threat of cancer of oral cavity and a cannabis dependence syndrome [3-4]. Bachs et al. (2001) have reported the onset of acute cardiovascular fatalities following cannabis consumption [5]. Dumont et al. (2009) have suggested the increase in the heart rate and temperature in humans consuming cannabis [6]. S. Menahem (2013) has reported the occurrence of cardiac asystole following the usage of cannabis [7]. Although the effect of cannabis products on the activity of the heart has been reported, we did not come across many studies that explain the physiology of the ANS and the alteration in the electrophysiology of the heart. Recurrence analysis helps in the qualitative analysis of the temporal variations in any time series data [8]. Dodds et al. (2017) have reported that HRV analysis can be used as a non- invasive method to understand the physiology of the ANS [9]. ECG signals provide information about the electrical activity of the heart and has been extensively studied for the diagnosis of the cardiovascular disorders in the last few decades [10]. Aqil et al. (2015) have reported the use of joint time- frequency analysis (including wavelet transform) for ECG signal processing [11]. Gautam et al. (2016) have proposed artificial neural network (ANN) based approach for classification of ECG signals [12]. Taking a note of the aforementioned facts, the current study proposes the qualitative analysis of the heart activity and stability of the heart rate using recurrence analysis of RRI series. This was followed by HRV and ECG signal analysis to understand the changes in the ANS and the cardiac electrophysiology in the women abusing bhang (a product of cannabis). Hereafter, bhang will be regarded as cannabis, unless stated otherwise. II. REQUIREMENTS ECG clamp electrodes (BPL Medical Technologies Pvt. Ltd., India), Vernier EKG sensor (Vernier Software and Technology Pvt. Ltd., USA), Vernier protoboard connector (Vernier Software and Technology Pvt. Ltd., USA), NI USB 6009 DAQ (National Instruments, USA), and LabVIEW (V13, National Instruments, USA) were used for the acquisition of the ECG signals. The processing of the ECG signals was carried out using LabVIEW, and the analysis of the ECG- derived signals (e.g. RRIs) and parameters was performed Suraj K Nayak, Karan Pande, Pratyush K Patnaik and Kunal Pal * 1 Dept. of Biotech & Medical Engg., NIT-Rourkela, Odisha, India-769008 * kpal.nitrkl@gmail.com Anilesh Dey Dept. of Electronics & Communication Engg. Kaziranga University, Jorhat, Assam, India-785006 Shankar J Patel Jagnyaseni Hospital, Jharsuguda, Odisha, India-768201 Arfat Anis Dept. of Chemical Engg. King Saud University, Riyadh, Saudi Arabia- 11421 Shikshya Nayak Dept. of Electrical Engg. & EEE VSSUT, Burla, Odisha, India-768018 Proceedings of APSIPA Annual Summit and Conference 2017 12 - 15 December 2017, Malaysia 978-1-5386-1542-3@2017 APSIPA APSIPA ASC 2017