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BackgroundThe variations in Tridoshas are the basis for disease diagnosis and treatment in Ayurveda. The doshas are assessed by sensing the pulse manually with fingers which depends on skill of the physician. There is a need to measure doshas using instruments and study them objectively.ObjectiveArterial stiffness is well established pulse parameter in modern medicine and is closely associated to kathinya in the context of Ayurveda. The aim of our study was to measure arterial stiffness using Nadi Tarangini, a pulse acquisition system, and investigate the significant variations of stiffness across Tridosha locations.Materials and methodsA total of 42 samples of vata, pitta and kapha pulses with proper systolic and diastolic peaks were included in the study. The arterial stiffness parameters namely stiffness index (SI) and reflection index (RI) were considered for the study. The data was analyzed using one-way ANOVA followed by Tamhane's T2 test. The changes in SI and RI between males and females were assessed using independent samples t test.ResultsSI at vata (5.669 ± 1.165) was significantly low compared to pitta (8.910 ± 3.509) and kapha (8.021 ± 2.814); RI at vata (0.846 ± 0.071) was significantly low compared to pitta (0.945 ± 0.043) and kapha (0.952 ± 0.033). SI at kapha was significantly low in females compared to males.ConclusionThe SI and RI acquired using Nadi Tarangini have shown significant variations across Tridosha locations. The framework developed to measure the arterial stiffness across Tridosha locations can be used for the interventional studies in Ayurveda which in turn can help in disease diagnosis and treatment.

Assessment of individual constitution ( prakriti ) has been an important basic construct of the Ayurveda system of medicine. The AyuSoft prakriti diagnostic tool has been extensively used in Ayurveda research. However, we could not find any literature regarding reliability of a prakriti diagnostic tool in patients with psychiatric conditions. One hundred and twelve patients (M = 70) suffering from various psychiatric disorders as per ICD-10 criteria were recruited (Depression = 31; Schizophrenia = 30, Anxiety disorders = 27; OCD = 9; BPAD = 15). The AyuSoft tool (developed by C-DAC, Pune, India) was applied to determine their prakriti after obtaining written informed consent. Two Ayurveda physicians independently assessed prakriti of the same patients through clinical examination. Inter-rater reliability was assessed between prakriti scores obtained from AyuSoft and those from the Ayurveda physicians by determining Cohen’s Kappa intra-class correlation coefficient (ICC). ICC estimates and their 95% confidence intervals were calculated using SPSS statistical package (version 24.0) based on a mean-rating ( k = 2), consistency and two-way mixed-effects model. We observed that there was a significant correlation between dosha scores obtained through AyuSoft and those from the two Ayurveda physicians (for all three doshas : p < 0.01). Inter-rater reliability was moderately strong for vata (ICC = 0.72; Cronbach’s alpha = 0.83), good for pitta (ICC = 0.58; Cronbach’s alpha = 0.62) and comparatively weak for kapha dosha (ICC = 0.44; Cronbach’s alpha = 0.51) respectively. Prakriti diagnosis by AyuSoft was feasible in stabilized psychiatric patients and was found comparable to clinical diagnosis of prakriti by Ayurveda physicians in patients with psychiatric disorders.

Yoga philosophy includes the theory of Tri-guna (three mental traits): sattva (signifies a tendency to ‘goodness’), rajas (tendency towards ‘activity’), and tamas (tendency towards “inertia”). This cross-sectional study aimed to understand the differences in the expression of gunas in patients suffering from major psychiatric disorders (n = 113, 40 females) and age-gender-education-matched healthy controls (HCs; n = 113, 40 females). Patients were diagnosed by a psychiatrist using DSM 5 criteria and suffered from the following disorders: depression (n = 30), schizophrenia (SCZ; n = 28), obsessive–compulsive disorder (OCD; n = 23), anxiety (n = 16), and bipolar affective disorder (BPAD; n = 16). Tri-gunas were assessed using a validated tool (Vedic Personality Inventory) and symptoms were assessed using standard scales as per the diagnosis. Multi-variate analysis of variance (MANOVA) was used to assess the differences in guna scores between HCs and patients, and between patients with different diagnoses. A two-tailed Pearson correlation was performed between the gunas and psychometric scales. Results revealed that HCs had significantly higher sattva traits as compared to patients (except those with OCD). Each psychiatric diagnosis also showed a specific guna configuration: (1) Anxiety disorders and OCD: High sattva-rajas, low tamas; (2) Depression: High sattva-tamas, low rajas; (3) Psychotic disorders (SCZ/BPAD): High tamo-rajas, low sattva. Significant positive correlations were observed between rajas traits and anxiety/OC/positive psychotic symptoms, negative psychotic symptoms and tamas traits, and sattva traits and OC symptoms. This finding has clinical implications, both to develop ways of predicting outcomes of psychiatric disorders, as well as to develop psycho-therapeutic and lifestyle interventions targeting the gunas.