Post mortem cooling of the body and estimation of time since death.
ABSTRACT Estimation of time since death in the field of forensic medicine expertise is an issue of high interest, especially in case of violent death caused by unknown executor. Post mortem cooling of the body is one of the pertinent parameters in estimation of time since death during the early postmortem period. Purpose of this paper is to analyze some of the existing methods, compare obtained results and determine which method gives more precise results of the estimation of time since death. This paper presents the analysis of 50 cases autopsied at the Institute of Forensic Medicine and Criminology in Skopje, with known time of death. Rectal temperature was taken with digital thermometer. Simultaneously, environment temperature was measured as well as the body weight; it was recorded whether the body was covered or naked. In order to estimate time since death following methods were applied: Method I, Method II, Al-Alousi and Anderson and Henssge- nomogram. Comparison of the known time of death with the time obtained by the applied methods has shown a discrepancy of few hours. Comparison of results obtained by application of the above stated methods has shown that the Henssge-nomogram gives less discrepancy from the true time of death.
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ABSTRACT: Model-based methods play an important role in temperature-based death time determination. The most prominent method uses Marshall and Hoare's double exponential model with Henssge's parameter determination. The formulae contain body mass as the only non-temperature parameter. Henssge's method is well established since it can be adapted to non-standard cooling situations varying the parameter body mass by multiplying it with the corrective factor. The present study investigates the influence of measurement errors of body mass m as well as of variations of the corrective factor c on the error of the Marshall and Hoare-Henssge death time estimator t (D). A formula for the relative error of t (D) as a function of the relative error of m is derived. Simple approximations of order 1 and 0 nevertheless yield acceptable results validated by Monte Carlo simulations. They also provide the rule of thumb according to which the quotient of the standard deviations D(t (D)) of the estimated death time and D(m) of the body mass is equal to the quotient of the estimated death time t (D) and the body mass m (D(t (D))/D(m) ≈ t (D)/m). Additionally, formulae and their approximations are derived to quantify the influence of Henssge's body mass corrective factor c on death time estimation. In a range of body masses between 50 and 150 kg, the relative variation of the body mass corrective factor is approximately equal to the relative variation of the death time (Δt (D) = (t (D)/c)Δc). This formula is applied and compared to computations and to experimental cooling data with good results.Deutsche Zeitschrift für die Gesamte Gerichtliche Medizin 02/2011; 125(3):437-44. · 2.69 Impact Factor
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ABSTRACT: Temperature-based methods represent essential tools in forensic death time determination. Empirical double exponential models have gained wide acceptance because they are highly flexible and simple to handle. The most established model commonly used in forensic practice was developed by Henssge. It contains three independent variables: the body mass, the environmental temperature, and the initial body core temperature. The present study investigates the influence of variations in the input data (environmental temperature, initial body core temperature, core temperature, time) on the standard deviation of the model-based estimates of the time since death. Two different approaches were used for calculating the standard deviation: the law of error propagation and the Monte Carlo method. Errors in environmental temperature measurements as well as deviations of the initial rectal temperature were identified as major sources of inaccuracies in model based death time estimation.Deutsche Zeitschrift für die Gesamte Gerichtliche Medizin 07/2011; 125(4):503-17. · 2.69 Impact Factor
- Journal of Indian Academy of Forensic Medicine. 12/2012; 34(4-4):292-294.