NeuroReset Research

Posted by NeuroReset Inc. March 11th, 2020
  • Risk of falls with the elderly has become widely focused amongst medical researchers.
  • Postural instability associated with age and a number of balance disorders typically stem from a deterioration or failure of peripheral sensory systems.
  • Excess coronal and sagittal body sway equating to fall risk can be accurately assessed using APDM technology. (7)
  • Preliminary studies are showing NeuroConnect wearable devices reduce postural sway significantly.

Falls account for:


a year in direct healthcare costs in Canada alone (8)


of all hip fractures (9)


of seniors’ injury-related hospitalizations (10)

Until now, there has been no wearable technology to help improve sensory perception

with hope of reducing the risk of falls.

Risk of Falls

Postural Sway Research using Neuro ConnectTM Wearable technology

The high incidence of serious falls among elderly people has prompted many researchers to investigate age related changes in postural control. Research in this area has indicated that aging has detrimental effects on postural control, which cause an increase in body sway (1–3).

The World Health Organization advises that falls are the second leading cause of accidental or unintentional injury deaths worldwide. (4)

Adults over 65 years of age suffer the greatest number of fatal falls. (5)

Globally, the older adult population will exceed 1.6 billion by 2050. 1/3 to 1/2 of them will fall at least once annually. (6)

It is likely that older adult falls will remain the number one cause of disability, hospitalization, and injury-related death…… and a “fear of falling” dramatically reduces the quality of life. (6)




We have used APDM’s advanced wearable sensors to collect and analyze the effects of Neuro Connect™ Balance, NC ONE and LifeStyle devices.

Hundreds of universities and hospitals use the APDM system worldwide. This technology is involved in 224 published research papers and is the most trusted wearable Gait and Balance assessment system on the market.(11)

We measured postural sway using APDM opals (sensors) and a footplate designed to standardize the stance width for each test.

All test results are compared against the baseline of what is considered a normal 95% Ellipse Sway area which is formulated from normal Coronal Sway, and normal Sagittal Sway.

Postural sway measures are assessed using the Opal movement sensors placed on a subject’s lumbar spine and both ankles: all metrics are reported in Coronal, Sagittal and Transverse planes.

In these initial studies, a range of individuals both males and females in different age categories took part.

Research Methodology

Standing in sock feet astride the footplate, the person is asked to stand for 30 seconds while staring at a single position on the wall 6 feet away. The person is asked to stand with hands at their side in a relaxed fashion, breathing calmly without speaking.

The first three tests are done wearing a sham device. The third of the three sham device tests is selected as the baseline against which the Balance, NC ONE and LifeStyle devices are measured.

Test Sequence

  1. Sham device
  2. Sham device
  3. Sham device (results selected as baseline)
  4. Balance clip and/or
  5. NeuroConnect ONE single clip and/or
  6. Neuro Connect LifeStyle 3 clips set.

A baseline for each person is automatically generated to compare against normative values which is graphically indicated by the grey elliptical region on chart.


TEST PATIENT #1: Female, Age 81 with balance concerns. The grey ellipse is considered normative. Body sway outside the grey ellipse is considered abnormal.

Baseline test
No device
Normative: .00490-.0420
Result: .0501

Balance clip
Normative: .00490-.0420
Result: .0179
Improvement 61.3%

Enhanced Balance Clip
Normative: .00490-.0420
Result: .0208
Improvement: 58.5%

TEST PATIENT #2: Male, Aged 75. Healthy and active in sports but describes balance concerns. The grey ellipse is considered normative.

Baseline test
No device
Normative: .00490-.0420
Result: .0347

Balance clip
Normative: .00490-.0420
Result: .0200
Improvement  42.4%

Normative: .00490-.0420
Result: .0199
Improvement: 42.7%

LifeStyle Clips
Normative: .00490-.0420
Result: .0169
Improvement: 51.3%

TEST PATIENT #3: Male, age 47. Extremely fit retired professional athlete. The grey area is normative.

Baseline Test
No device
Normative: .00490- 0.0420
Baseline: .0200

NC ONE single clip
Normative: .00490- 0.0420
Result: .0268
No improvement
minus 34.0%

LifeStyle set of 3 clips
Normative: .00490- 0.0420
Result: .0121
Improvement: 39.5%

TEST PATIENT #4:  Male, age 68. Gait and balance concerns. The grey area is normative.

Baseline Test using Sham Device
Normative Ellipse Sway: .00490- 0.0420
Baseline: 0.184

Balance Device (enhanced)
Normative Ellipse Sway: .00490- 0.0420
Result: 0.155
Improvement 15.6%

NC ONE single device
Normative Ellipse Sway: .00490- 0.0420
Result 0.704
Improvement: 61.7%

LifeStyle devices
Normative Ellipse Sway: .00490- 0.0420
Result 0.143
Improvement: 22.3%

TEST PATIENT #5:  Female, age 70 with balance concerns. The grey area is normative.

Baseline Test: No Device
Normative Ellipse Sway: .00490- 0.0420
Baseline: 0.0122

Balance Device
Normative Ellipse Sway: .00490- 0.0420
Result: 0.155
Improvement 69.7%

About Neuro Connect ™ Devices

  • Mark Metus is the inventor of Neuro Connect TM technology and president of NeuroReset Inc.
  • He has been a chiropractor for over 36 years and specializes in Applied Kinesiology.
  • The technology is the result of 8 years of research using Functional Neurological testing on patients.
  • The properties of the infused devices were consistently found to improve the functional test results. The findings suggested the devices in some way affected or improved the function of the central nervous system.
  • Two different frequency patterns were tested. Based upon years of functional neurology testing the first pattern (NeuroConnect Balance) appears to upgrade the attentiveness of the cerebellum to response to sensory input related to balance.
  • The second pattern (NeuroConnect ONE and LifeStyle) appears to influence proprioceptive nerve fibre receptor response resulting in the motor cortex improving muscle response.


  • APDM technology has been used to verify these findings.
  • Extensive research is presently being carried out on Gait and Balance using standardized testing procedures including Sway, TUG, CTSIB etc., as well a COM (centre or mass) evaluations using Force Plate technology and 3D camera assessment.


  • The technology which involves infusing the devices with a frequency pattern was developed by Dr Metus and a team of physicists.
  • He is also the developer of the QAT (Quantum Alignment Technique) a method of diagnosis and treatment.
  • NeuroReset is the winner of the Pinnacle Award for the best new invention in golf at the 2017 PGA Merchandise Show.


Recommended Use

Daily use for improved cerebellar and motor cortex response during normal activities as well as for enhancing neuromuscular response while doing Geri-Fit training and other fall risk prevention programs. See list at this link:

About Neuro Connect ™ Devices


(1) Perrin PP, Jeandel C, Perrin CA, Béné MC.  Influence of visual control, conduction, and central integration on static and dynamic balance in health older adults.  Gerontology. 1997;43:223-231

(2)  Whipple R. Wolfson L, Derby C, Sing D, Tobin J. Altered sensory function in balance in older person.  J Gerontol. 1993;48(special issue):71-76

(3) Berg K. Balance and its measure in the elderly; a review. Physiother Can. 1989;41:240-246

(4) World Health Organization > www.who.into/en/news-room/fact-sheets/detail/falls.

(5) PMC US National Library of Medicine, National Institutes of Health, Journal List > Chiro Man Therapy, V.23:2015, PMC4308009.

(6) He W, Goodkind D, Kowal P, U.S. Census Bureau, International Population Reports . An aging world: 2015. Washington, DC: U.S. Government Publishing Office; 2016.

(7) Mobility Lab by APDM, White Paper

APDM Wearable Technologies/publications/.  Featuring Opal wearable sensors:

  1. Aziz, et al. “Distinguishing NearFalls from Daily Activities with Wearable Accelerometers and Gyroscopes Using Support Vector Machines.” IEEE EMBS Conference 2012.
  2. Deshmuckh, et al. “Enhancing Clinical Measures of Postural Stability with Wearable Sensors.” IEEE EMBS Conference 2012.
  3. Florentino, et al. “Hierarchical Dynamic Model for Human Daily Activity Recognition.” Universidad Carlos III de Madrid. 2012.
  4. Rigsby, Bigelow. “Validation of a Commercial Wearable Sensor System for Accurately Measuring Gait on Uneven Terrain.” University of Dayton. 2012.
  5. “A Wearable Motion Analysis System to Evaluate Gait Deviations.” University of South Florida. 2013.
  6. Aziz, et al. “The Effect of Window Size and Lead Time on Pre-Impact Fall Detection Accuracy Using Support Vector Machine Analysis of Wait Mounted Inertial Sensor Data.” IEEE. 2014.
  7. Cristiani, et al. “A Wearable System for Measuring Limb Movements and Balance Control Abilities Based on a Modular and Low-Cost Inertial Unit.” IEEE. 2014.
  8. Lee, et al. “Inertial Sensing-Based Pre-Impact Detection of Falls Involving Near-Fall Scenarios.” IEEE. 2014.
  9. Buckley, et al. “Attenuation of Upper Body Accelerations During Gait:  Piloting an Innovative Assessment Tool for Parkinson’s Disease.” University of Sheffield. 2015.

(8,9,10) Government of Canada, Seniors Falls in Canada stats.


Results from Pilot Studies


Nov 2018


Clinical research was conducted by NeuroReset Inc. using APDM technology at three separate facilities located in New Jersey USA, Ottawa Canada ON and Collingwood ON Canada. Statistical results have not yet been verified by external examiners.


Please note

  • All results we compared to baseline findings (the median of 3 sham devices which did not contain an infusion). The test subjects did not know which clips they were wearing when tested.
  • Lack of improvement is indicated by a minus sign i.e., Ellipse – 0.9
  • Sagittal Sway movement: forward and backward sway
  • Coronal Sway movement: left and right sway
  • Ellipse: indicates the area covered by the combination of sagittal and coronal sway.

Important: Published research has shown that excess sagittal and coronal sway (i.e., combined movement outside the normal ellipse area) equates to an increase in fall risk.

Increased sway: High Fall Risk


Decreased sway: Low Fall Risk


Testing before and after wearing devices on a firm surface. The pilot are studies summarized below.

May 14, 2018                 

Sway testing

41 people tested 15 Male 26 Female

Sway testing (38 of 41 tested)

  • 92.7% responded to at least one product.

LifeStyle clip results:

  • 2.4% coronal improvement,
  • 7.3% sagittal improvement
  • 14.6% ellipse improvement*

NC One clip results:

  •  2.4% coronal improvement
  • 2.4% sagittal improvement
  • 2.4% ellipse improvement

Balance clip results:

  • -4.9% coronal (less than baseline – (no improvement)
  • -2.4% sagittal(less than baseline (no improvement)
  • 2.4% ellipse improvement
  • 2/3 of the people either M/F responded to Balance and Lifestyle.
  • 80% males responded to NC One while only 38.5% females responded


*LifeStyle clips offer 14.6 overall ellipse improvement

May 14 2018

 TUG Test

“Timed Up and Go”

35 people tested 15 Male 20 Female

TUG testing is a standard test used in research to measure gait and balance in the older population and community dwelling older adults.


  • 82.8% Faster duration
  • 74.3% Faster turn duration
  • 77.1% More forward lean (a sign of improvement)
  • 85.7% Increase in turn velocity
  • 71.4% Faster sit to stand
  • 80.0% Faster stand to sit


LifeStyle and Balance performed better than NC ONE.

June 2018

Young Athletes Study

33 people tested 31 Males  2 Females Average age 19


Sway Testing conducted with Balance and NC One

  • 67% responded to either NC One or Balance, 30% responded to both products.
  • Coronal improved 6% with both products
  • Ellipse improved 12.1% with both products
  • Overall 75.7% had better coronal improvement
  • Overall 81.8% had better ellipse

            T-Test for Balance significance results*

   94% Coronal    99.9% Sagittal      98.3% Ellipse


T-Test for NC One was not significant .

* Awaiting external validations

June 2018

Unnamed Study*

*We are not permitted to state clinical conditions

19 people tested 10 Males / 9 Females

52.6% of those tested responded to both products

Sway testing

Balance:  15.8% sagittal improvement

LifeStyle: 10.5% sagittal improvement

Baseline ellipse showed no improvement with either Balance or LifeStyle

TUG testing (18 took part)

  • All 6 parameters improved
  • 94% faster duration
  • 61.1% faster turn duration
  • 66.7% more forward lean (good)
  • 61.1% increased turn velocity
  • 44.4% faster sit to stand
  • 83.3% faster stand to sit

Overall it appears that LifeStyle performed better.

June/July 2018

June 26 – July 10th Study

 21 people: 8 Males and 13 Females

Sway test: 66.7% responded to the products

Balance: + 4.8% coronal, – 4.8 sagittal and +4.8 ellipse

NC ONE: +19.1% coronal, 0 sagittal, +4.8% ellipse

LifeStyle: +19.1% coronal, -14.3 sagittal,

+14.0% ellipse

TUG test:


  • 57.1% Faster duration
  • 61.9% Faster turn duration
  • 47.6% More forward lean (good)
  • 38.1% Increase in turn velocity
  • 38.1% Faster sit to stand
  • 42.9% Faster stand to sit

July 2018

Seniors Residence Study

33 people tested 12 males and 21 females

Average age 76 years

Sway test:

72.7 of the people responded to devices

Balance: +12.1% coronal improvement

+ 6.1% sagittal improvement

+ 15.2% ellipse improvement

NC ONE: + 6.1% coronal improvement

– 3%. No sagittal improvement

+15.2% ellipse improvement

LifeStyle: no improvements

Conclusion: Balance and NC One performed better in

this age category.

Assessing Postural Sway Using a Foam Surface to Induce Perturbations

Abstract: Our previous pilot studies demonstrated changes in coronal, sagittal and ellipse sway before and after wearing devices while standing upright on a firm surface for 30 seconds. We refer to this as a passive assessment of postural sway. This study examines coronal, sagittal and ellipse sway before and after wearing clips while standing on a 4 inch foam surface. We refer to this test as an active assessment of postural sway. This study required the candidates to actively maintain their balance while standing upright for 30 seconds on a foam surface. We randomly selected 22 people with an age range of 32-76 of which 17 were female and 5 male (average age 63.7). Everyone was in good health, 3 had chronic conditions we are not allowed to mention. Candidates were tested using APDM technology to measure Sagittal, Coronal and Ellipse sway while standing on a firm surface and then a foam surface for 30 seconds with and without devices. LifeStyle devices were used in the test.


Sagittal sway (forward and backward) reduced by 7.27
Coronal sway (side to side) reduced by 16.32
Ellipse sway (the combination of forward and backwards and side to side sway) reduced by 24.02%.

Summery of Findings

The significance (P= values) indicate this did not happen by chance. See Table1

Conclusions: Seniors balance and fall risk research has concluded that as we age, we have a tendency to increase forwards and backwards postural sway which increases our risk of falling. Preliminary research suggests Neuro Connect devices reduce combined postural sway by up to 24% and therefore may reduce the risk of falling.

Discussion: The human body is designed to respond to the biomechanical demands standing upright and initiate movements to carry out other activities requiring stability and balance.  It has multiple sensory systems to assist with postural control to prevent us from falling. The interactive mechanisms that contribute to good balance are the vestibular, visual and somatosensory systems of our body. The vestibular system contributes to our spatial orientation, the visual contributes to dimension awareness and perspective, and the somatosensory system sends information from specialized nerve receptors embedded in muscles and joints. All this information is processed by the central nervous system and used to correctly maintain postural integrity and balance when we carry out everyday activities.  If any of these inputs become defective or fail, then body sway will increase and muscle activity will increase concurrently, in order to maintain the balance of the body. (1) Numerous research studies have been undertaken to assess how balance and stability are maintained. (2)

There is extensive research on the study of balance and postural control systems and it has yielded helpful information about their interaction. (3)  In general, body sway is considered a worthwhile parameter to measure in order to determine fall risk in seniors.  Stability is assessed as a function of the amount of postural sway of the human body. The assessment of body sway in the standing position has been carried out using cameras to measure the degree of sagittal and coronal movements. Force plates are used to calculate the displacement of the centre-of-mass (COM) which is determined by the centre of pressure (COP) excerpted on the force plate.  Research carried out by Tarantola et al, using a stabilometric platform indicated that the human body tends to shift towards a safer position with minimum expenditure to reduce body sway (4)

Commissais, et al. examined balance control in the standing position using a servo-driven moving platform to ensure controlled repeatable movements. (5) Ghahramani, et al recognized the needed to assess postural control of older people to determine their risk of falling. They quantified the amount of postural sway of the human body using an MTw motion sensor strapped over the lumbar-sacral junction to measure forward and backward movements. The analysis of the angular deviation signal obtained from the sensor mounted on the pelvis provided an indication of the postural balance control, body sway of a subject and accordingly the risk of fall. (6) Maki et al used a force plate to induce small pseudorandom platform motions to perturb balance in the induced-sway tests which included (a) spontaneous postural sway, (b) induced anterior-posterior sway, (c) induced medial-lateral sway, (d) anticipatory adjustments preceding volitional arm movements, (e) timed one-leg stance, and (f) performance on a clinical balance assessment scale. They were able to determine that lateral spontaneous-sway amplitude was found to be the single best predictor of future falling risk suggesting that control of lateral stability may be an important area for fall-preventative intervention. (7) Horak et al suggest that movement monitors are worn on patients during functional balance and gait assessments now allow accurate assessment of balance and gait impairments to guide and track rehabilitation. (8) Using postural sway metrics is a better predictor of fall risk than stopwatch measures of standing in particular postures. A recent technical advance in movement monitors for physical therapists is sophisticated software algorithms that calculate useful balance and gait measures by combining the information from the three dimensional (3D) accelerometer, 3D gyroscope, and magnetometer signals. (9) J Howcroft et al assessed 100 older adults (75.5 ± 6.7 years) stood quietly with eyes open and then eyes closed while Wii Balance Board data were collected. Range in anterior-posterior (AP) and medial-lateral (ML) center of pressure (CoP) motion; AP and ML CoP root mean square distance from mean (RMS); and AP, ML, and vector sum magnitude (VSM) CoP velocity were calculated. They concluded that static posturography measures can discriminate between elderly fallers and non-fallers. (10)

Seniors and Falling a Statistical Review: The USA and Canada

May 2018 the US Centre for Disease Control and Prevention released a report titled Deaths from Falls amount Persons Aged 65 and Above.

  • Deaths from unintentional injuries are the seventh leading cause of death among older adults, and falls account for the largest percentage of those deaths.
  • Approximately one in four U.S. residents aged ≥65 years (older adults) report falling each year, and fall-related emergency department visits are estimated at approximately 3 million per year.*
  • In 2016, a total of 29,668 U.S. residents aged ≥65 years died as the result of a fall (age-adjusted rate = 6 per 100,000), compared with 18,334 deaths (47.0) in 2007.
  • The rate increased in almost every demographic category included in the analysis, with the largest increase per year among persons aged ≥85 years.

CDC Conclusions and Recommendations

  • The CDC recommended that Health care providers should be aware that deaths from falls are increasing nationally among older adults but that falls are preventable.
  • Falls and fall prevention should be discussed during annual wellness visits when health care providers can assess fall risk, educate patients about falls, and select appropriate interventions.
  • As the population of persons aged ≥65 years in the United States, increases, the rising number of deaths from falls in this age group can be addressed by screening for fall risk and intervening to address modifiable risk factors such as polypharmacy or gait, strength, and balance issues.(11)

Stats Canada released a report titled Understanding seniors’ Risk of Falling and Their Perception of Risk, citing that falls are the most common cause of injury among older Canadians. (12)

  • Every year, it is estimated 1 in 3 seniors aged 65 years and older are likely to fall at least once.
  • Falls are also one of the leading causes of injury-related hospitalizations among seniors and contributed to 73,190 hospitalizations during 2008–2009.
  • Each year, hospitalizations due to falls account for approximately 85% of injury-related hospitalizations for seniors.
  • According to the Public Health Agency of Canada, over one-third of seniors who are hospitalized as a result of a fall are placed in long-term care.
  • The consequences of falls later in life can be serious, resulting in hospitalizations, reduced quality of life, chronic pain, injuries such as hip fractures, and increased risk of death.
  • In Canada, in 2008–2009, 35% of fall-related hospitalizations among seniors involved a hip fracture.

Stats Canada conclusions and recommendations

This report came to some important conclusions about age and risk associated with the perception of falling which are worth noting.

  • In 2008–2009, more than three-quarters of seniors (78%) had a low risk of falling, and 22% had a high risk of falling.
  • More women than men perceived a risk of a fall, and the proportion of seniors who perceived a risk tended to increase with age. About 34% of seniors reported perceiving a risk of a fall.
  • Most seniors had a correct perception of their risk of falling. However, about 2 in 10 seniors overestimated their risk, while about 1 in 10 underestimated it.
  • Seniors’ perceptions of their overall health could be related to their perception of their risk. In some cases, their perception of overall health may have been related to overestimating or underestimating their risk. Seniors who underestimated their risk of a fall were more active and were less likely to be diagnosed with three or more chronic conditions. Seniors who overestimated their risk of a fall were more likely to live alone and have a diagnosis of three or more chronic conditions.
  • Fall risk is multifactorial but age is certainly a common denominator.


(1) A. Nardone, J. Tarantola, A. Giordano, M. Schieppati, “Fatigue effects on body balance”, Electroencephlography and Clinical Neurophysiology, vol. 105, 1997, pp. 309-320

(2) A. L. Hof, M. G. J. Gazendam, W. E. Sinke, “The condition for dynamic stability”, Journal of Biomechanics, vol. 38, 2005, pp. 1-8

(3) Influence of stimulus parameters on human postural responses. H. C. Diener, F. B. Horak, and L. M. Nashner Journal of NeurophysiologyVolume 59, Issue 6 1988 Jun 01

(4) J. Tarantola, A. Nardone, E. Tacchini, M. Schieppati, “Human stance stability improves with the repetition of the task: effect of foot position and visual condition”, Neuroscience Letters, vol. 228, 1997, pp. 75-78

(5) D. A. C. M. Commissaris, P. H. J. A. Nieuwenhijzen, S. Overeem, A. de Vos, J. E. J. Duysens, B. R. Bloem, “Dynamic posturography using a new movable multidirectional platform driven by gravity”, Journal of Neuroscience Methods, vol. 113, 2002, pp. 73-84

(6) Impact of Age on Body Postural Sway. M Ghahramani, F Naghdy, D Sterling, G Naghdy. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, Australia

(7) B. Maki and P. Holliday,”A Prospective study of Postural Balance and Risk of Falling in an Ambulatory and Independent Elderly Population,”
Journal of Gerontology: Medical Sciences,vol. 49,no. 2,pp. 72-84, 1994.

(8) Horak, et al. “Potential of APDM Mobility Lab for the Monitoring of the Progression of Parkinson’s Disease.” Expert Review of Medical Devices. 2015

(9) Role of Body-Worn Movement Monitor Technology for Balance and Gait Rehabilitation Fay Horak, Laurie King and Martina Mancini
PHYS THER. Published online December 11, 2014 Originally published online December 11, 2014

doi: 10.2522/ptj.20140253

(10) Howcroft J, Edward D.Lemaire,  Jonathan Kofman, Elderly fall risk prediction using static posturography. William E. McIlroy PLOS ONE | DOI:10.1371/journal.pone.0172398 February 21, 2017

(11)  Morbidity from Fall Among Persons Aged ≥ 65 Years -United States, 2007- 2016. Weekly/May 11, 2018 / 67(18); 509-514.

(12) Understanding seniors’ risk of falling and their perception of risk. Caryn Pearson, Julie St-Arnaud, Leslie Geran, Health Statistics Division Release Date: October 2014.

Determining the Effects of Neuro ConnectTM Spray on Individual’s Strength: A Pilot Study

Mike Hoban BSc., Alexander Woinski OMS-II, Chuck Moris PhD, Dr Igor Nazarov PhD Jan 2020

In total, 32 individuals were put through the same 25-30 minute vigorous workout, using Medex selectorized equipment, to eliminate the chance for the warm-up effect to impact the results. They were then examined on an ARX machine. The machine gave accurate leg press Max Power and Max Force readings before and after using a Neuro Connect treated shirt. The average change in Force across all participants between the control test and when wearing the Neuro Connect treated shirt increased by 12.4%. A T-test yields a (P<.0005). There was a subsequent increase in the average Max Power generated across all participants, equating to 9.7% (P<.0005).


The primary hypothesis of this paper is that specific light wave patterns can influence the neurological system of human beings, and in the case of Neuro Connect devices, wearing them makes the entire system respond more efficiently. This also implies that, at certain times and under varying circumstances, parts of the system function at a lower level than physiologically possible at the level of the proprioceptive nerve components. In other words, decreased proprioceptive feedback leads to reduced muscle response and inadequate muscle response leads to joint strain. In 2010, the Neuro Connect effect was discovered and in 2017 with collaboration with physicist Dr. Igor Nazarov, Neuro Connect devices were developed and presented to the public. To better understand the effects and underlying mechanisms of the Neuro Connect devices, private studies were done by NeuroReset Inc.,, and published on the company’s website. Patients with an inadequate response to the assessment techniques before wearing devices appeared to perform normally when they attached the Neuro Connect devices to their shirt and shoes. The results were supported studies using APDM wearable movement and kinematic sensor technology. Multiple trials were run on patients and the data was collected to determine their ability to stand still for 30 seconds. The amount of side-to-side sway (coronal sway) and front to back sway (sagittal sway) was first recorded using APDM. The combination of coronal and sagittal sway was collated by the APDM technology to give a computer readout of the entire ellipse formed during the 30-second test. Seen in Figure 1 below, the grey region is considered a normal range of motion, the blue line describes the average outer range of patient movement, and the black line is the actual patient movement. Next, the subjects were tested using wearable Neuro Connect technology. The ellipses in Figure 1 demonstrate the before and after changes, showing the effects of 3 different Neuro Connect devices on sway. The studies were replicated many times and presented as a hypothesis that biophoton emitting devices somehow improve proprioception.

At present, proprioception can be defined as the cumulative neural input to the Central Nervous System from specialized nerve endings called mechanoreceptors, which are located in the joints, capsules, ligaments, muscles, tendons, and skin.1 Proprioception alludes to the perception of tension/force, body/joint movement, and the relative position of limbs. Proprioception is generally divided in the sub modalities; sense of tension (resistance), sense of movement, and joint position sense. Sense of resistance represents the ability to appreciate force generated within a joint. Sense of movement refers to the ability to appreciate joint movement, including the duration, direction, amplitude, speed, acceleration and timing of movements. Joint position sense determines the ability of the subject to perceive a presented joint angle and then, after the limb has been moved to actively or passively reproduce the same joint angle. All three modalities can be appreciated consciously and unconsciously, contributing to automatic control of movement, balance, and joint stability, and thus being essential to carry out daily living tasks, walking, and sports activities.2 Any improvement of proprioceptive ability can greatly assist a person with performance difficulties or sub-optimal performance. Neuro Connect devices contain specific wave patterns that transmit particular corrective biophotons to the wearer with the goal of improving proprioception.

Evidence for the existence of coherent excitations in biological systems came from the study of biophotons.3,4 All organisms emit and store light from a coherent photon field within the living system. The concept of a morphogenic field was introduced into biology by Alexander Gurwitsch (1874-1954). He examined the morphogenetic movements of large cell collectives during formation of the different organs. He concluded that the cells move and re-orientate as if being attracted by some unknown force. The advent of genetics provided, for some, an explanation for this finding via the discovery and understanding of Hox genes, SHH, and more. However, in recent times geneticists and biologists believe there is some unknown connection between the code within our cells and the theory of the morphogenic field that may be generated as cells replicate. The spontaneous self-assembly of a living being into intricate patterns of functional form largely remains a mystery that scientists are quickly unraveling. While most current research seeks explanations in terms of genetic and molecular activities, a viable alternative view already exists. Living organisms have the

Summery of Findings

capacity to behave as Electro Magnetic (EM) resonators, trapping within themselves EM fields in the form of spatial energy patterns. These patterned energy fields are called resonant modes and are a rich source of long-range information capable of guiding biological pattern formation from an early developmental stage. Focusing on plants, the so-called living crystals of the world, a comparison of tissue and EM resonant mode patterns reveals striking similarities. The concept of EM energy resonators is not limited to plants, but may extend to single cells, water droplets, other organisms, and whole planets.5 It was hypothesized that the internal electro magnetic field of biological systems is coherent and that this coherence plays a significant role in pattern formation of the biological system.6,7 Freely available MRI data of structural components of human brain from different universities were studied and used to build actual structural database of the brain, including neural network connectome data, blood vessel map, ventricles, cavities for cerebral-spinal fluid, and hippocampus regions of midbrain. A rigorous dielectric resonance simulation was run to verify the hypothesis that a scale-free resonance does exist in the material architecture of the brain. The conclusion of the study speculates that there may exist a unified geometric pattern hidden in the vibrational frequencies of the brain components, which hold important information for the brain’s informational processing.8

While this is just scratching the surface on the available research regarding biological frequencies, light and wave patterns, and biophotons and how they might interact with human physiology, it provides a framework for the possible underlying mechanisms in which Neuro Connect devices might work through. In summary, the goal of our pilot study is to determine if the light resonating devices set to specific frequency patterns stimulate or upgrade sub-optimal proprioceptor response, as to be measured by the amount of force generated through an isometic leg press. Given the current availability of technology and measurement devices, we are unable to determine if the frequency patterns emitted by the devices operate within the dynamics which contribute to the morphogenic operation of cell structure or if the nature of devices acts upon to the actual architecture of the brain or if there is some other mode of operation.


Thirty two (32) participants (17 male and 15 female) volunteered for the study at their local gym. All 32 individuals were put through the same 25-30 minute vigorous workout, using Medex selectorized equipment, to eliminate the chance for the warm-up effect to impact the results. Following the completion of the session, participants performed a 10-second isometric leg press on an ARX Alpha machine (see figure 2), which measured their power and force, with their eyes closed to prevent them from seeing the ARX display screen. Next, Neuro Connect was applied to the subject by having them wear a frequency-treated shirt. While wearing the Neuro Connect shirt, subjects retested the ten-second isometric leg press and the new data was collected. Post-Neuro Connect results were compared to the control results.


Please see Table 1.
1) The Average Force (no shirt) denotes the average strength exerted during the initial 10 second leg press.
2) The Average Force (w/shirt) is the average strength exerted while wearing the treated shirt during the second 10 second test.
3) The Maximum Power (no shirt) is the result when not wearing the shirt while doing a leg press.

4) The Maximum Power (w/shirt) is the maximum power exerted during the second 10 second leg press while wearing the treated shirt.
5) The Percentage Increased Force is the percentage increase in the maximum force exerted during the exercise.
6) The Percentage Increase Power is the percentage maximum power exerted during the leg press.

To give a clearer explanation of the results, we will describe A3 results, as an example. The equations for force and power are represented in Table 2. Prior to wearing the treated shirt she recorded a force of 809.6 ft/ lb. When she wore the treated shirt her result was 1150 ft/lb which represented a 29.6% increase in force. Her maximum power increased by 38.6% from baseline, that is, without wearing the treated shirt. The average of all of the participants’ values comparing baseline numbers to the results when wearing the treated shirt shows an increase of 12.4% in force output and a 9.7% power increase. This was significant enough to deduce an influence of the treated shirt on the force and power of the participants.

As can be seen by Table 1, the average change in Force across all participants between the control test and when wearing the Neuro Connect treated shirt is an increase of 12.4%. A T-test yields a P Value of <.0005. In the adjacent column, it can be seen that there was a subsequent increase in the average Max Power generated across all participants, equating to 9.7% (P<.0005).

While the T-test is the preferred method of statistical analysis for our study, we realize that our data set does not fall under a normal distribution. While the T-test assumes a normal distribution of means, we cannot place full validity in this parametric test. To supplement this, we ran the data through the Kruskal-Wallis test, a nonparametric measure. Setting possible outcomes as simply an increase or a decrease from control to experimental, the Kruskal-Wallis test yields a P Value of <.0001 for both Force and Power. Taking it a step further, with the understanding that a small change in Force and Power generated from control to experimental could be due to random chance and variance, we performed the Kruskal-Wallis test again with three potential outcomes; an increase, a decrease, or no-change (defined as a change <5%). Again, the test revealed P Values of <.0001 for both Force and Power.


It has been discussed that the two main functional goals of postural behaviour are postural orientation and postural equilibrium. Postural orientation involves the active alignment of the head and trunk in relation to gravity, support surfaces, the visual surround and internal references. Incorporated with this is sensory information from somatosensory, vestibular and visual systems. The extent to which these inputs are incorporated depend upon the goals of the movement task and the environment in which it is performed. Postural equilibrium is owed to the coordination of the body’s movement strategies to stabilize the center of gravity during internal and external stability disturbances.9 A separate study done on stance stability and sway concluded that with repetition of a task, the body learns and adapts by shifting its mass toward a safer position, allowing for a minimizing of energy expenditure as a result of reduced corrections of sway.9 One can link that observation to our scenario to claim that the body may have engaged more core function or control when wearing the treated shirt. Similar results were seen in Neuro Reset’s prior APDM study where there was a dramatic reduction in the coronal and sagittal sway when wearing Neuro Connect devices. Concurrently concluded was that forward leaning and decrease in sway are independently occurring processes that might be a result of improved central integration of proprioceptive input.10 This allows us to extrapolate that improved awareness of body position through improved proprioceptive response might be responsible for the increased force and power output, which we will equate to an increase in strength. Given that the results yielded participants recording higher output values in both categories when wearing the treated shirt, it is prudent to conclude that the resonant frequencies delivered by the treated shirt caused an increase in strength gain and also an increased workload. This all supports our hypothesis that Neuro Connect devices improve proprioception, but it cannot be definitively concluded that this was the method by which strength and workload increases resulted. Future studies will have to be directed more toward a proprioceptionspecific outcome.Regardless of the underlying mechanism, the results of the study showed an increase in the measured values of force and power by the participants when wearing the Neuro Connect treated shirt compared to their trials without. Because of the implications of these variables, Neuro Connect devices can prove to be beneficial for athletes of all kinds, as well as any individual or group looking to improve on or maximize physical performance for any purpose. If the underlying mechanism behind the improved results with Neuro Connect do relate to an increase in proprioception, an even wider audience can serve to benefit from the product.


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(8) Complete Dielectric Resonator Model of Human Brain from MRI Data: A Journey from Connectome Neural Branching to Single Protein Pushpendra Singh, Kanad Ray, D. Fujita and Anirban Bandyopadhyay Chapter in Lecture Notes in Electrical Engineering · January 2019 DOI 10.1007/978-981-13-1642-5_63

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DARI Motion delivers sub-millimeter accuracy from scan-to-scan so trainers can establish an athlete’s motion baseline, and objectively track changes over time.

Twelve pitchers took part in this study using the DARI motion capture system. They first performed 15 pitches and the readings were recorded. They were then given HoloTypeTM shirts infused with Neuro Connect to wear and each ankle was sprayed with NC ActiveTM spray. Each pitcher threw another 15 pitches, and the results were recorded and displayed below. There was an improvement of 10.18% of overall joint function plus improved ball speed.