Biofield Frequency Bands-Definitions and Group Differences

Overview

Journal Glob Adv Health Med

Specialty Public Health

Date 2022 Apr 8

PMID 35392431

Authors

Jens Rowold

Paul D Hewson

Affiliations

Soon will be listed here.

Abstract

Background: In the biofield literature, it is suggested that electromagnetic energy is part of the biofield. However, little is known about the exact definition of potential electromagnetic biofield frequency bands (FBs).Primary Study Objective: The current study sought to identify biofield FBs and test potential group differences.Methods/Design: High-frequency (i.e. >200 Hertz) voltage was measured at body parts along the spine and the brain.

Setting: Measurements were conducted in an electrically shielded laboratory.

Participants: Twenty experienced biofield practitioners (BPs, sample 1) and twenty-four students (STs, sample 2) participated in the study.

Interventions: The BPs performed a wide set of biofield exercises, while the STs participated in an assessment centre (with exercises such as role play). A total of =342 exercises were performed.Primary Outcome Measures: Based on surface electromyography, high-frequency (i.e., >200 Hertz) voltage was utilized as outcome measure.

Results: 10 FBs were identified across all the data sets. The BPs had higher spectral power across these bands compared to the STs.

Conclusion: The present paper presents a replicable method for the assessment of electromagnetic FBs which are potentially useful for future biofield research.

References

Hammerschlag R, Jain S, Baldwin A, Gronowicz G, Lutgendorf S, Oschman J . Biofield research: a roundtable discussion of scientific and methodological issues. J Altern Complement Med. 2012; 18(12):1081-6. DOI: 10.1089/acm.2012.1502. View

Ross C, Harrison B . The use of magnetic field for the reduction of inflammation: a review of the history and therapeutic results. Altern Ther Health Med. 2013; 19(2):47-54. View

Warber S, Gordon A, Gillespie B, Olson M, Assefi N . Standards for conducting clinical biofield energy healing research. Altern Ther Health Med. 2003; 9(3 Suppl):A54-64. View

Rubik B, Muehsam D, Hammerschlag R, Jain S . Biofield Science and Healing: History, Terminology, and Concepts. Glob Adv Health Med. 2015; 4(Suppl):8-14. PMC: 4654789. DOI: 10.7453/gahmj.2015.038.suppl. View

Mima T, Hallett M . Corticomuscular coherence: a review. J Clin Neurophysiol. 1999; 16(6):501-11. DOI: 10.1097/00004691-199911000-00002. View

Hintz K, Yount G, Kadar I, Schwartz G, Hammerschlag R, Lin S . Bioenergy definitions and research guidelines. Altern Ther Health Med. 2003; 9(3 Suppl):A13-30. View

Miwakeichi F, Martinez-Montes E, Valdes-Sosa P, Nishiyama N, Mizuhara H, Yamaguchi Y . Decomposing EEG data into space-time-frequency components using Parallel Factor Analysis. Neuroimage. 2004; 22(3):1035-45. DOI: 10.1016/j.neuroimage.2004.03.039. View

Yan A, Zhou W, Yuan Q, Yuan S, Wu Q, Zhao X . Automatic seizure detection using Stockwell transform and boosting algorithm for long-term EEG. Epilepsy Behav. 2015; 45:8-14. DOI: 10.1016/j.yebeh.2015.02.012. View

van Aerde K, Mann E, Canto C, Heistek T, Linkenkaer-Hansen K, Mulder A . Flexible spike timing of layer 5 neurons during dynamic beta oscillation shifts in rat prefrontal cortex. J Physiol. 2009; 587(Pt 21):5177-96. PMC: 2790257. DOI: 10.1113/jphysiol.2009.178384. View

10.

Delorme A, Makeig S . EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004; 134(1):9-21. DOI: 10.1016/j.jneumeth.2003.10.009. View

11.

Bigdely-Shamlo N, Mullen T, Kothe C, Su K, Robbins K . The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Front Neuroinform. 2015; 9:16. PMC: 4471356. DOI: 10.3389/fninf.2015.00016. View

12.

Rubik B . The biofield hypothesis: its biophysical basis and role in medicine. J Altern Complement Med. 2003; 8(6):703-17. DOI: 10.1089/10755530260511711. View

13.

Van Wijk E, Van Wijk R, Bajpai R . Quantum squeezed state analysis of spontaneous ultra weak light photon emission of practitioners of meditation and control subjects. Indian J Exp Biol. 2008; 46(5):345-52. View

14.

Fels D . Endogenous physical regulation of population density in the freshwater protozoan Paramecium caudatum. Sci Rep. 2017; 7(1):13800. PMC: 5653844. DOI: 10.1038/s41598-017-14231-0. View

15.

Freeman W, Holmes M, Burke B, Vanhatalo S . Spatial spectra of scalp EEG and EMG from awake humans. Clin Neurophysiol. 2003; 114(6):1053-68. DOI: 10.1016/s1388-2457(03)00045-2. View

16.

Buzsaki G, Draguhn A . Neuronal oscillations in cortical networks. Science. 2004; 304(5679):1926-9. DOI: 10.1126/science.1099745. View

17.

Islam M, Rastegarnia A, Yang Z . Methods for artifact detection and removal from scalp EEG: A review. Neurophysiol Clin. 2016; 46(4-5):287-305. DOI: 10.1016/j.neucli.2016.07.002. View

18.

Scott-Phillips T . Defining biological communication. J Evol Biol. 2008; 21(2):387-95. DOI: 10.1111/j.1420-9101.2007.01497.x. View

19.

Allen A, Kennedy P, Cryan J, Dinan T, Clarke G . Biological and psychological markers of stress in humans: focus on the Trier Social Stress Test. Neurosci Biobehav Rev. 2013; 38:94-124. DOI: 10.1016/j.neubiorev.2013.11.005. View

20.

Aoyagi Y, Stein R, Branner A, Pearson K, Normann R . Capabilities of a penetrating microelectrode array for recording single units in dorsal root ganglia of the cat. J Neurosci Methods. 2003; 128(1-2):9-20. DOI: 10.1016/s0165-0270(03)00143-2. View