Exercise-based cardiac rehabilitation (CR) plays a vital role in improving function and preventing mortality of cardiovascular disease (CVD) patients. Outpatient (Phase II and III) CR is almost nonexistent in India because of several reasons such as time, cost, distance, education level, scarcity of resources and so forth. Cardiologists or cardiac surgeons can directly advise patients and their family members to do an optimal dose of exercise in low-resource settings, that is, rural, low-income, or low-educated patients. Talk test is a no-cost, subjective tool for exercise prescription which is gaining popularity in CR because of its simplicity. This brief descriptive review covers history, administration, physiological mechanisms, reliability and validity, and safety among cardiac patients along with limitations of the ‘talk test’. This review also theoretically discusses how the talk test could be used in primary and secondary prevention of CVD. Finally, it advocates Indian CR team to use this simple validated tool as a self-monitoring tool of exercise intensity.

An extended instrumental variable (EIV) method is considered for the stochastic Hammerstein system (ARMAX and general model structure). The EIV method provides consistent parameter estimates by eliminating noise-induced bias in the least square (LS) method. To estimate the parameters, the Hammerstein model is formulated using the bilinear parameterization. The bilinear model is identified by introducing the nonlinear instrumental variables obtained from transformed delayed outputs using nonlinear mapping and polynomial basis of delayed inputs. These instruments are analyzed in full generality by computing the bounds on expected relationship between instruments and noise for the general noise disturbance structure. Then, a specific case with hyperbolic tangent (tanh) transformation is considered. Comparative performance analysis of the proposed IV method with the existing IV method, the data filtering-based LS methods, and the extended LS method shows improvement in the statistical properties of parameters estimates.

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