Aims and objectives:
1. To show an objective evidence for the action of Homeopathic medicine by measuring physiological variability
in human body temperature.
1. To draw signature for individual Homeopathic medicines.
2. To find out a unified method to select homeopathic medicine for diseased individuals.
3. To introduce objective measures into Homeopathic system of medicine like data loggers and sensors to measure physiological variability for selection of Homeopathic medicine.
Introduction and review:
Homeopathy is a well-described, scientifically based system of approaching health and disease. “Scientific” because the insights are based on reproducible experiments. “Well-described” because from these observations a number of precise basic fundamental rules became evident, first among them the “similarity principle.12 “But lack of objective evidence for the action of Homeopathic medicine bestow an opportunity for skeptics to comment ridiculously.
Although homeopathy is only 200 years old, it is now practiced in a variety of ways, most of which bear little resemblance to what Hahnemann taught. In the public mind the word “homeopathy” has become so vague that for some it means only an “alternative medicine” and for others a combination of homeopathic medicines that you buy in the health food store, one mixture for allergies, another for headache, etc12. There by it needs a unified method to select similar homeopathic medicine for a patient’s disturbed energy field.
Our earth by virtue of a hidden invisible energy, carries the moon around her in twenty eight days and several hours, and the moon alternately, in definite fixed hours (deducting certain differences which occur with the full and new moon) raises our northern seas to flood tide and again correspondingly lowers them to ebb.3
According to the homeopathic way of thinking, a disease originates from a disturbance of the patient’s “vital force.” This is the life force energy that sustains life. As the origin of disease occurs on this energetic level, the homeopathic remedy has also to be on this level.12 The current study provides objective evidence for the action of homeopathic medicine and also deals with identification of similar homeopathic medicine for the patient’s disturbed life force by means of objective measures, “Data loggers and Sensors”.
This study facilitates in the drawing signatures for individual Homeopathic medicines. This study also gives you an idea about approach, to develop a common method to select accurate Homeopathic medicine for diseased individuals.
In order to recognize the behavior of homeopathic medicines, which are applied orally, it is attempted to study the natural regulatory mechanisms in the Human body as well as in nature.
In this regard Biorhythms, “occurrence of cyclical biological events”, have supported the hypothesis that “Homeopathic medicines produce cyclical change in the human body”. Extension of this initiative guide to the study of the function of the Hypothalamus “the seat of biorhythms”.
The hypothalamus is responsible for certain metabolic processes and other activities of the Autonomic Nervous System. It synthesizes and secretes neuro-hormones, often called hypothalamic-releasing hormones, and these in turn stimulate or inhibit the secretion of pituitary hormones. The hypothalamus controls body temperature, hunger,
thirst, fatigue, and circadian cycles.9
The tiny dose of Homoeopathic Medicines to some extent move up the thermoregulatory set point located in the Hypothalamus of living beings naturally required for the rise in body temperature in order to deactivate the microbes (Disease Forces).13
The effects of tiny doses of Homoeopathic Medicines simulate the Biologic Activities of Pyrogenic Cytokines like IL-1, TNFa, AND IL-6 and INFs. The potentised dose of similar Homeopathic Medicines (just like PGE2) is the most potent of fever-producing means, without inflicting any injurious effect to the sick living being when prescribed on symptom similarity and in infinitesimal low doses.13
So one of the regulatory functions of the Hypothalamus, ‘Thermoregulation in human subjects’ is taken as the primary subject to understand the action of Homeopathic medicine. The parameter “Physiological variability in human body temperature” (Vital Heat) is selected for the study.
The history of the study of variations in the physiological parameters goes back to 18th century, when Stephen Holes documented beat to beat variability. He related spontaneous fluctuations in the peripheral blood flow to adjustment in the continuous circulation by the thermoregulatory system.2
Thermoregulation is the ability of an organism to keep its body temperature within certain boundaries, even when the surrounding temperature is very different. This process is one aspect of homeostasis: a dynamic state of stability between an animal’s internal environment and its external environment.10
The organism that thermoregulates is one that keeps its core body temperature within certain limits. It was not until the introduction of thermometers that any exact data on the temperature of animals could be obtained. It was then found that local differences were present, since heat production and heat loss vary considerably in different parts of the body, although the circulation of the blood tends to bring about a mean temperature of the internal parts. Hence it is important to identify the parts of the body that most closely reflect the temperature of the internal organs. Also, for such results to be comparable, the measurements must be conducted under comparable conditions. The rectum has traditionally been considered to reflect most accurately the temperature of internal parts, or in some cases of sex or species, the vagina, uterus or bladder. Occasionally the temperature of the urine as it leaves the urethra may be of use. More usually the temperature is taken in the mouth, axilla, ear or groin.10
The body owns a regulatory system that keeps body temperature within a close range. The centers of this system are located in the hypothalamus. Temperature sensors are found in the preoptic and anterior hypothalamic nuclei. More sensors are contained in the skin and in a few deep tissues in the body. The temperature is regulated by a nervous feedback mechanism. The signals from the sensors are evaluated in the posterior hypothalamus.5
In this study, temperature is measured from the skin of the forearm. As this study doesn’t require exact values, the variability in temperature is measured from skin. “It is supposed that Homeopathic medicines produce change in temperature variability”.
Materials and methods:
A. Temperature Data logger,
B. Water/Soil Temperature Sensors ,
C. PC & Green line data logging software.
D. Human Subjects.
E. Homeopathic Medicines of 200C Dilution.
F. Statistical Processing Software for Data Analysis.
2. Temperature Datalogger Specifications:
i. Measurement range: -40 to 1580 F
ii. Accuracy: + or – 0.63 0F ( from 320 to 1220 F)
iii. Resolution : 0.050 F at 770 F
iv. Response time in airflow of 1 m/s : 6 minutes
v. Operating temperature: -40 to 1580 F(logging), 320 to 1220 F(Launching/Readout)
vi. Memory: 64 bytes
vii. Weight: 46g(1.6 oz)
3. Water/Soil Temperature Sensor Specifications:
i. Measurement range: -400 to 1220 F in water, -400 to 2120 F in air.
ii. Accuracy: + or – 0.450 at 650 F
iii. Resolution: 0.050 F at 680 F
iv. Response time in airflow of 1 m/s: 3 minutes, 30 seconds in water.
v. Operating range: sensor tip and cable immersion in fresh water up to +1220 F.
vi. Material: Housing stainless steel sensor tip.
vii. Probe dimensions: 0.5cm X 2.5cm
The experiment was conducted with Human subjects. Freshly medicated 6-9 Homeopathic pills were applied orally half an hour prior to the acquired temperature readings. Temperature readings were obtained from the skin of the forearm of the subjects. A water soil sensor was connected to the skin by means of cellophane tape. Readings were taken in the sitting posture. Subjects were instructed not to move while obtaining readings. Method of connecting data logger and sensor was shown in Fig 2.
Temperature readings were taken at an interval of 1 second for 5 minutes. Each data file of a subject contains 300 readings. After obtained readings, data can be exported to an excel file. Each data file contains 300 temperature reading points i.e. Temperature variability data.
Two types of protocols are followed in these experiments.
5.1. With Placebo control: Subjects are divided into the medicine group and the placebo group. Homeopathic medicine is applied to one group and placebo to another group. E.g.: Exp No:1, Exp No:2, Exp no:6, & Exp no:7.
5.2. Without Placebo control: Subjects are not divided into groups. Reading are taken from the same subjects before and after applied homeopathic medicine. E,g,: Exp No 3, Exp No:4, Exp no:5, Exp no:8 & Exp No:9.
6. Statistical Analysis:
The temperature variability data is processed with statistical processing software. The statistical procedures Auto regressive spectrum (AR Spectrum) and Parametric Reconstruction and Prediction (PRP) are used for the data analysis. With these procedures the time series data can be converted into frequency domain data.
In statistical signal processing and physics, the spectral density, power spectral density (PSD), or energy spectral density (ESD), is a positive real function of a frequency variable associated with a stationary stochastic process, or a deterministic function of time, which has dimensions of power per Hz, or energy per Hz. It is often called simply the spectrum of the signal. Intuitively, the spectral density captures the frequency content of a stochastic process and helps identify periodicities.14
In physics, the signal is usually a wave, such as an electromagnetic wave, random vibration, or an acoustic wave. The spectral density of the wave, when multiplied by an appropriate factor, will give the power carried by the wave, per unit frequency, known as the power spectral density (PSD) of the signal. Power spectral density is commonly expressed in watts per hertz (W/Hz) or dBm/Hz.14
For voltage signals, it is customary to use units of V2Hz−1 for PSD, and V2sHz−1 for ESD or dBμV/Hz.14
For random vibration analysis, units of g2Hz−1 are sometimes used for acceleration spectral density.14
6.1 Autoregressive model:
The notation AR(p) refers to the autoregressive model of order p. The AR(p) model is defined as
where are the parameters of the model, c is a constant and is white noise. The constant term is omitted by many authors for simplicity.
An autoregressive model can thus be viewed as the output of an all-pole infinite impulse response filter whose input is white noise.
Some constraints are necessary on the values of the parameters of this model in order that the model remains wide-sense stationary.8 For example, processes in the AR(1) model with |φ1| ≥ 1 are not stationary. More generally, for an AR(p) model to be wide-sense stationary, the roots of the polynomial must lie within the unit circle, i.e., each root zi must satisfy | zi | < 1.
The Parametric Interpolation and Prediction is a powerful composite algorithm that generates a parametric (sinusoids or damped sinusoids) model of the signal. The algorithm has three stages. In the first stage, an AR, Prony, Eigenanalysis, or Fourier procedure is used to estimate the frequencies and component count. In the second stage a linear fit is made to determine the amplitudes and phases. These are the starting estimates for the third stage, the non-linear optimization. This option combines all of the steps into a single integrated procedure for interpolation and prediction.
6.2.1 Non-Linear Optimization Plot:
The following is the non-linear optimization graph for data consisting of three sinusoids and noise. The three component functions are shown in the Y-axis plot. The Y2 plot contains the fitted curve and the data that were fitted.
Figure 3: Example graph of parametric prediction.
The following are results of the experiments conducted with various Homeopathic
A) EXP No: 1
Experiment with Gelsemium 200C:
In case of experiment with Gelsemium, there were 8 subjects, 4 days, and two subjects per day. This experiment was conducted with 2 sensors.
Figure 4 : Gelsemium 200C and Placebo Readings, original temperature variability graphs.
In the following figure:5 there are two columns: left side are Gelsemium 200C subjects, right are Placebo subjects. Placebo control is used in this experiment.
Sensor 1 –
subject 1 – Gelsemium 200 – time 07.40.14 am – 08.00.00am
Sensor 2 –
subject 2 – placebo – time 07.40.14 am – 08.00.00am
Sensor 1 –
subject 3 – Gelsemium 200 – time 07.40.14 am – 08.00.00am
Sensor 2 – subject 4 – placebo – time 07.40.14 am – 08.00.00am
Figure 5: AR Spectrum Gelsemium and placebo given subjects.
Sensor 2 –
subject 5 – Gelsemium 200 – time 07.40.14 am – 08.00.00am
Sensor 1 –
subject 6 – placebo – time 07.40.14 am – 08.00.00am
Sensor 2 –
subject 7 – Gelsemium 200 – time 07.40.14 am – 08.00.00am
Sensor 1 –
subject 8 – placebo – time 07.40.14 am – 08.00.00am
In this Experiment, the skin temperature is recorded form the skin of the forearm for 10 minutes at an interval of 2 seconds.
In case of Gelsemium subjects – observe, peaks in medium frequency are at the same frequency level. But amplitude is different in case of sensor 2 Gelsemium subjects (first column last two graphs).
B) EXP No:2
Experiment with Sulphur 200C:
In case of experiment with Sulphur 200C, there are 6 subjects, 4 days and two subjects per day. This experiment also used 2 sensors.
Figure 6: Temperature variability graphs of Sulphur 200C and Placebo
Sensor 1 –
subject 1 – Sulphur 200 – time 8.00.00am – 8.10.00am
Sensor 2 –
subject 2 – placebo – time 8.00.00am – 8.10.00am
Sensor 1 –
subject 3 – Sulphur 200 – time 8.00.00am – 8.10.00am
Sensor 2 –
subject 4 – placebo – time 8.00.00am – 8.10.00am
7: AR Spectrum for Sulphur 200C and Placebo subjects.
Sensor 1 –
subject 5 – Sulphur 200 – time 8.00.00am – 8.10.00am
Sensor 2 –
subject 2 – placebo – time 8.00.00am – 8.10.00am
Sensor 1 –
subject 6 -Sulphur 200 – time 8.00.00am – 8.10.00am
Sensor 2 –
subject 2 – placebo – time 8.00.00am – 8.10.00am
In this experiment skin temperature was recorded from the forearm for 10 minutes at an interval of 1 second.
Figure: 7 showing 2 columns of graphs. The left side column is Sulphur given subjects. The right side is of placebo given subjects. The medium frequency (marked) shows peaks at the same frequency level, amplitude also does not vary much.
In case of the experiment with Gelsemium, placebo subjects applied alcohol mixed sugar pills.
In case of experiment with Sulphur, placebo subjects applied just sugar pills.
Note: alcohol also produces peaks in medium frequency but not at a fixed frequency level as the medicine produced. Observe the above graphs. (Fig: 5, Fig: 7)
Parametric reconstruction and prediction graph for the above Sulphur 4 subjects: This graph shows 2 persons (Subject 2 and Subject 4) responded well to Sulphur 200C.
Figure 8: Parametric Spectrum for Sulphur 200C given subjects.
C) EXP No: 3
Experiments with China 200C:
This experiment includes 5 subjects, parametric reconstruction graphs for 3 of these subjects, before and after China 200C is applied are presented here:
Subject 1: Smoothness and regular pattern in the Parametric y2 plot after applied homeopathic medicine represents the remedy action.
Figure 9: Before and after China 200C – subject 1
Figure 10: Before and after China 200C – subject 2
Subject 2: Before and after China 200C.
Subject 3: Before and after applied China 200C.
Figure 11: Before and after China 200C – subject 3
D) EXP No: 4
Experiments with other Homeopathic medicines:
i. The following picture shows graphs containing original temperature readings along with parametric prediction graph which is before and after applied Calcarea carb 200C.
Figure 12: Before and after Calcarea carb 200C
ii. The following picture shows graphs containing original temperature readings along with parametric prediction graph which is before and after Lachesis 200C.
Figure 13: Before and after Lachesis 200C
iii. The following picture shows graphs containing original temperature readings along with parametric prediction graph which is before and after Pulsatilla 200C.
Figure 14: Before and after Pulsatilla 200C
iv. The following picture shows graphs containing original temperature readings along with parametric prediction graph which is before and after Lycopodium 200C.
Figure 15:Before and after Lycopodium 200C
v. Parametric Spectrum after applied Bacillinum 200C:
Figure 16: Parametric Spectrum after Bacillinum 200C.
E) EXP No: 5
Experiments with some more Homeopathic medicines: The wave pattern in the Parametric Spectrum changed to smooth curves after applied homeopathic medicine like Natrum muriaticum, Kali carbonicum, Lycopodium, Alumina etc.
In this experiment homeopathic medicines of freshly medicated 6 pills are applied orally, readings are taken after 15 minutes. The last two graphs are from subjects without applying any medicine.
Figure 17: Parametric Spectrum after Homeopathic Remedy.
More Experiments and graphs are mentioned in annexure 1
1) It can be observed from the above graphs that the irregular pattern in the Parametric graph is changed to a smooth curve after applied homeopathic medicine. The change in graph pattern is observed within 30mits of applied homeopathic medicine.
2) The appearance of a pair of peaks in medium frequency of the AR Spectrum is the indication for Homeopathic medicine action.
In this study, the results of 45 Homeopathic medicines’ before and after action, is represented in the form of graphs. 23 (51%) subjects showed change in the Parametric Spectrum. 25 (55%) subjects showed change in the AR Spectrum. More results can be observed in annexure 1. The results discussed are only trail phase experiments.
Homeopathic medicine is considered to be a placebo due to the absence of medicinal substance beyond 1×10^-12 dilution, but this work reveals how Homeopathy works.
The change in graph patterns which are evident from the above results and observations is stanchly a clue for the action of Homeopathic medicines.
In case of experiments with Gelsemium 200C, all the 4 subjects (Exp no: 1) who received medicine, produced changes in the AR Spectrum (Fig:5). The appearance of a pair of small peaks in medium frequency of the AR Spectrum is an indication for the action of homeopathic medicine. This experiment is conducted with placebo control. The placebo given subjects failed to produce a pair of peaks in the medium frequency (Fig:5). The thing
to observe in this experiment is that the readings are taken at the same time of day.
The first day’s placebo subject produced peaks as like the Gelsemium subject (Fig: 5). This might be the result of the placebo and Gelsemium 200C subjects sitting close together while they obtained temperature readings.
In case of experiments with Sulphur 200C (Exp no: 2) as like the Gelsemium subjects, all four subjects who have received medicine produced change in the AR Spectrum(Fig:7), whereas the placebo given subjects failed to produce peaks in medium frequency.
The Parametric Spectrum (Fig:8, Exp no:2) of 2 subjects out of 4 Sulphur 200C subjects showed changes in the wave pattern. This shows the sensitivity of the parametric prediction and reconstruction method. The graph pattern is easily disturbed by external impressions.
The medium frequency peaks of the AR Spectrum produced in the case of experiments with Gelsemium and Sulphur are do not appear at the same frequency level in other experiments. The reason is that the readings are taken at the same time of the day in the case of the above mentioned Gelsemium and Sulphur experiments, but not in the case of other experiments. It shows that the homeopathic medicine action also depends on the time of day. So it is not possible to produce the AR Spectrum for all the mentioned remedies.
The change in pattern of variability produced by some homeopathic medicines, observed through the AR Spectrum, is not reflected in the Parametric Spectrum. It may be due to the difference in sensitivity of the AR Spectral procedure and the Parametric Spectrum.
In case of experiments with China 200C (Exp no:3) only 3 out of the 5 subjects showed a change in the variability pattern in the Parametric Spectrum (Fig: 9,10,11).
In case of experiments with other medicines (Exp No:4), there is also a clear change in the pattern of the parametric reconstruction graph after application of the homeopathic medicine.
Out of 45 subjects applied homeopathic medicine, 23 subjects (51%) showed change in the Parametric Spectrum. 25 subjects (55%) showed change in the AR Spectrum. Those subjects who have not showed a change in the AR Spectrum showed a change in the Parametric Spectrum and vice-versa. Results will be more favorable with sophisticated equipment (data loggers & sensors).
It is evident from the above experiments that Homeopathic medicines produce certain changes in physiological variability. Homeopathic medicines have a straight impact on physiological phenomenon of living organisms. The physiological functions in living organisms are under control of the Hypothalamus. So this work of measuring physiological variability in the human body temperature after giving homeopathic medicine shows that the homeopathic medicines are acted on by the Hypothalamus. The physiological functions are influenced by homeopathic medicines, so the wave pattern in the Parametric reconstruction graphs in the above experiments are regular after applied homeopathic medicine. Indirectly it shows homeopathic medicines act on the Hypothalamus,
disturbs the functions of the Hypothalamus in the case of healthy subjects and sets right the disturbance in diseased
The numerical summary for the graph patterns is not represented. This needs some more observation and wide extended study. In the future this method of measuring physiological variability certainly offers quantification of Homeopathic medicine action.
The change in pattern of ‘Physiological Variability in the Human Body Temperature‘ after applied Homeopathic Medicine is an objective evidence for the action of Homeopathic medicine.
The experiment of measuring physiological variability in human body temperature is the straight answer for the mystery behind homeopathic medicine action. These experiments show Homeopathic medicine acts by producing change in physiological functions. The selection of homeopathic medicine by measuring physiological variability
in human body temperature will be a unified method in homeopathy. This work certainly introduces new techniques into the homeopathic system. The way of measuring temperature variability by data loggers and sensors for identification and selection of homeopathic medicine is one objective measure, introduced for the first
time in homeopathy.
This method can be used in Homeopathic pharmacies for testing quality & standardization of Homeopathic medicines. The extended studies based on this work can lead into identification of specific patterns among hydrogen bonds in Homeopathic dilutions.
The forth coming experiments based on present trials lead into identification of specific patterns for individual homeopathic medicines. The numerical values for obtained the specific pattern of the remedy will be a guide for the selection of indicated medicine for diseased individual. This kind of work also paves a path to develop a Computer program for the identification of homeopathic remedies.
1. Alex Hankey, Ph.D.:, “Are We Close to a Theory of Energy Medicine?” The Journal Of Alternative And Complementary Medicine, Volume 10, Number 1, 2004, pp. 83-86
2. Dr. Jindal & T.S. Ananthakrishnan: “Objective monitoring of response of Homeopathic medicines using medical analyzer”. BARC/2004/E/021.
3. Dr. Samuel Hahnemann: “Organon of Medicine“6th Edition, reprint 1997, translated by ‘William Boericke’ B. Jain publishers, P 99,
4. George Vithoulkas: “The science of Homeopathy” Reprint edition 1997, B Jain publishers, p128.
5. Guyton & Hall: “Textbook of Medical Physiology” 11th edition, Elsevier publisher.
6. Kiteny RI (1975): “An analysis of the non linear behavior of the human thermal vasomotor control system”, Journal of Theoretical Biology, 52, pp230-247.
7. Paranjape AS: (1989) : “Action of Homeopathic medicines : A Physicist’s view, Quarterly Bulletin of the central council for research in Homeopathy”, 10 p.26
Nov 19th , 2009. 11.35am
Nov 18th , 2009. 10.30am
Nov 19th , 2009. 11.35am
Nov 19th, 2009. 12.45am.
12. Dr. Tanwar: “Modus Operandii of Homeopathic Medicines in case of Pyrexial Diseases”
Nov 22nd 2009, 11.16 am.
Nov 18th, 2009. 11.50am
I am indebted to my parents; without their co-operation these experiments might not have seen the light.
I am grateful to Prof (Dr). C. Nayak, Director CCRH, for offered opportunity to improve my knowledge in research methodology.
I am obliged to Dr. N. Mistra and Dr. K. C. Muralidharan at RRI, Mumbai, discussions with whom enriched my knowledge in variability analysis. I am indebted to Dr. Jindal Head of Biomedical division, and Dr. Paranjape, solid State physics BARC, Mumbai, deliberations with whom improved my knowledge in statistical measures valid in time series analysis.
My exceptional gratitude towards Dr. Murali Krishna who helped and heartens me all through the experimental process. I am appreciative to Dr. Bhatia, administrator of hpathy.com, who encouraged me to write a
I am thankful to Prof (Dr). G. Yadagiri, Dr. P. Ramkrishnarao, Dr. Prabhavathi, Dr. M. D. Sreenivas, Prof. M. Srinivas who stands as inspiration for this work. I am indebted to my PG Colleagues in Hyderabad for their participation in experiments as subjects, to my patients in Machilipatnam clinic for their participation. I am very much thankful to my family members for their participation in these research trials.
My special thanks to Mr. Sadiq Mohammad and Mr. P. Ramakrishna who helped me in procuring equipment from abroad.
Experiments with some other Homeopathic medicines:
F) EXP No: 3
Figure 18: AR Spectrum before and after China 200C. China 200C: AR Spectrum for 5 subjects: Before and after applied China 200C
G) EXP No: 6
Experiment with Sulphur 200C: Sulphur 200C has given to 7 subjects and placebo to 5 subjects. Readings are taken from 8.00 – 8.10am. Below are two columns of graphs. Left column contains graphs of Sulphur 200C subjects, right side are of Placebo subjects.
Figure 19: AR Spectrum of Sulphur 200C and Placebo subjects.
H) EXP No: 7
Experiment with Sulphur 200C: AR Spectrum for Sulphur 200C and placebo subjects, readings are taken from 9.00am – 9.10am: Below are two columns of graphs. Left column contains graphs of Sulphur 200C subjects, right side are of Placebo subjects. Appearance of a pair of peaks can be observed in Sulphur 200C, First 3 subjects Fig 20.
Figure 20: AR Spectrum of Sulphur 200C and Placebo subjects.
I) EXP No: 8
Experiment with Lycopodium 200C: AR Spectrum for Lycopodium 200C given to 4 subjects:
Figure 21: AR Spectrum of Lycopodium 200C Subjects.
EXP No:1 Parametric Spectrum for Gelsemium 200C given to 4 subjects:
Parametric Reconstruction applied to the data of temperature variability obtained after applied Gelsemium 200C to 4 subjects.
4th graph shows that the person did not respond to the medicine.
Figure 22: Parametric Spectrum Gelsemium 200C Subjects.
J) Exp No 9:
Another observation, immediately after applied homeopathic medicine for patients: Below are the Parametric Spectrum for the variability readings taken immediately after applied indicated medicine Natrum muriaticum 200C and Pulsatilla 200C.
Figure 23: Parametric Spectrum before and after
applied Natrum Muriaticum 200C.
Figure 24: Parametric Spectrum before and after applied Pulsatilla 200C
Readers are requested to visit http://homeoresearch.blogspot.com for more graphs and information on this work.