Abstract
Study Objectives:
Poor sleep quality is a global public health issue. Technology approaches are desirable to patients and offer a potentially scalable solution to improve sleep health. The goal of this study was to test the effects of a novel wearable device for improving sleep.
Methods:
Participants with elevated scores on the Insomnia Severity Index (≥ 15) were recruited from social media advertisements and a university research study website. Eligible participants completed a baseline survey, wore a Fitbit, and completed sleep diaries for 1 week. Participants were randomly assigned to either an active or sham program (ie, same device but using nontherapeutic frequencies). Participants were asked to wear the device for at least 3 hours per day for 4 weeks. Devices were turned to active from 4 weeks until the final questionnaire assessment at 3 months. The primary outcome at 4 weeks was change in self-reported insomnia symptoms. Self-reported outcomes were also assessed at 3 months.
Results:
Participants in both the intervention and control groups experienced significant improvements in most self-reported sleep and daytime function measures. The intervention group reported greater improvement in diary-sleep efficiency. There was no significant change in Fitbit-assessed sleep.
Conclusions:
Results demonstrate high interest in the intervention and feasibility of the wearable device, but improvements in sleep and daytime function were observed in participants using the active and placebo devices.
Clinical Trial Registration: Registry: ClinicalTrials.gov; Name: A Novel Wearable Device for the Treatment of Insomnia; URL: https://clinicaltrials.gov/study/NCT05952297; Identifier: NCT05952297.
Citation:
Anderson DJ, Troxel WM, Landvatter J, Baron KG. A randomized pilot study of a wearable device using variable complex weak magnetic fields among participants with insomnia symptoms. J Clin Sleep Med. 2025;21(7):1285–1291.
Keywords: insomnia, technology, variable complex weak magnetic field, wearable
BRIEF SUMMARY
Current Knowledge/Study Rationale: This study tested a wearable device using variable complex weak magnetic fields among a sample of patients with insomnia symptoms, which is a novel method of insomnia treatment.
Study Impact: Results demonstrated improvement in insomnia symptoms and other outcomes among participants in both the intervention and control groups, but only the intervention group had improvements in sleep-diary-based sleep efficiency. Results demonstrate high interest in the intervention and feasibility of the wearable device, but large improvements were observed in participants using the active and placebo devices.
INTRODUCTION
Roughly one-third of the world’s population reports insufficient sleep duration, and as many as 70% report poor quality sleep,1 which can have impacts on an individual’s health and well-being.2,3 Insomnia is associated with an estimated $207.5 billion loss annually.4 Given the profound consequences, it is important to identify novel and scalable treatment options. Importantly, the frontline treatment for insomnia, cognitive behavioral therapy for insomnia,5 remains underutilized due a lack of specialty-trained providers, time, and resources.6 There is an acute need to identify safe, effective, and noninvasive treatments to improve sleep in those experiencing sleep disruptions and poor sleep quality, to promote sleep health across the continuum.7 There is a growing interest among patients for wearable devices for sleep.8 Such devices utilize different mechanisms, including neurofeedback, ultra-low radio frequency energy, vibration, and acoustic stimulation. Despite their popularity, most devices lack randomized studies to rigorously test their efficacy among populations who are experiencing sleep problems.
Recognizing this need, the current study investigated a novel device (Evolv28) designed to improve sleep through the application of variable weak magnetic frequencies. Evolv28 is a wearable sleep wellness device that contains coils that emit variable complex weak magnetic fields (VCMFs) through a neckband. The device generates VCMFs within the range of 0.1 to 10 milligauss. Electromagnets are positioned near the back of the user’s neck, targeting the posterior part of the superior cervical region just below the cranial cavity, to electromagnetically modulate the brainstem activity and influence a desired mental state. In principle, the brain wave patterns emulate the wave patterns emitted by the ferromagnets placed on the user’s neck adjacent to the brainstem. Variable weak magnetic frequencies are proposed to interact with neural activity by subtly altering the brain’s electromagnetic environment. Evolv28 is covered under the Food and Drug Administration’s guidelines for “General Wellness: Policy for Low Risk Devices” considered for general wellness use and presents a low risk to the safety of users and other persons.
The Evolv28 device is designed to be worn on the neck. Ferromagnets are positioned near the back of the user’s neck, targeting the posterior part of the superior cervical region just below the cranial cavity, to electromagnetically modulate the brainstem activity and influence a desired mental state, including, but not limited to, a sleep state, a calm and relaxing state, a creative state, or a stimulated state.
Results of an internal pilot study testing Evolv28 suggest that device users may experience reductions in perceived stress and anxiety.9 A similar device that emits extremely low frequency magnetic fields was previously tested to improve sleep and quality of life in patients with nocturia.10 Given strong associations among stress, anxiety, and poor sleep quality,11 the application of VCMFs may also have benefits for sleep quality. Preliminary studies have indicated that these frequencies can influence brainwave patterns associated with different sleep stages, suggesting their potential to enhance the restorative aspects of sleep.12–14 The goal of the current study was to conduct a randomized pilot study to evaluate the efficacy of the Evolv28 device for improving sleep among individuals reporting moderate to severe insomnia symptoms.
METHODS
Study design
The study was a randomized, double-blinded, placebo-controlled trial with a 4-week intervention period followed by a 2-month open-label follow-up period. Assuming a medium-to-large effect size (d = 0.74), the analysis determined that a total of 60 participants (30 per group) would be necessary to achieve 80% power to detect significant differences at a 2-sided alpha level of .05. This study was approved by the University of Utah Institutional Review Board (IRB_00165943) and registered on ClinicalTrials.gov (https://clinicaltrials.gov/study/NCT05952297).
Participants
Participants were recruited via social media. Inclusion criteria were age 18–65 years, read and write in English, smartphone user, and Insomnia Severity Index (ISI) score of ≥ 15. Participants were excluded if they had diagnosed sleep disorders other than insomnia (eg, sleep apnea or restless legs syndrome) or were currently receiving additional treatment for insomnia; had a history of serious mental health conditions (eg, Patient Health Questionnaire 8 score of > 15, psychosis, bipolar I, or the use of antipsychotic or mood-stabilizing drugs); had serious physical conditions (eg, current cancer treatment, neurological illness); drank >14 alcoholic beverages per week; used cannabis > 3 times in the past month; used any illicit street drugs; had a caffeine intake of > 400 mg per day; worked overnight more than once a month; had frequent headaches; was pregnant; or traveled across time zones > 3 times throughout the study period.
Procedure
All study procedures were performed remotely. Interested participants completed a screening survey; if eligible, a study coordinator contacted the participant to complete informed consent. After consent, study materials including the Evolv28 device, a Fitbit, and instructions were sent to the participant. Participants completed an instructional meeting with study staff, during which they reviewed baseline procedures and Fitbit setup. They then completed online surveys, including 7 days of daily electronic sleep diary surveys (SurveySignal), and wore the Fitbit for 7 days. After their baseline week, an unblinded staff member determined each participant’s group assignment and then sent that participant’s device serial number to programmers. Participants were randomly assigned 1:1 between intervention and control groups. The randomization table was generated using a random number table stratified by sex using permuted blocks of 4 to 6 participants. To begin the 4-week trial period, the study coordinator met with each participant to ensure the device was activated and confirmed the participant’s understanding of how to use it.
Participants wore the device around their necks, just below the cranial cavity, to electromagnetically modulate the brainstem activity, with the device resting on their shoulders, similar to wearing a pair of headphones around one’s neck. The intervention group received the active program (VCMFs within the range of 0.1 to 10 milligauss), and the control group received an inactive program (the device did not emit stimulation). In both conditions, the device and application appeared to be active according to the device and the application. The stimulation was not perceptible in either condition. Participants were asked to wear the device for at least 3 hours per day and while awake, not during sleep. The program was set to run for 3 hours to complete a session on the application but participants were able to meet the goal of at least 3 hours in more than one session if desired. If any technical issues occurred, the intervention time was extended to allow for at least 4 weeks of use before the postintervention assessment. Participant adherence to the Fitbit and Evolv28 was monitored by the study statistician throughout the trial, and reminders were sent to participants who were nonadherent in wearing either device for more than 2 days. At week 4, participants wore the Fitbit again for 7 days, completed electronic sleep diaries for 7 days, and completed follow-up surveys. After the posttrial assessment, all Evolv28 participants were transitioned to run the active treatment program between week 4 and 3 months. At the end of 3 months, participants completed online questionnaires.
Measures
Participants completed the following survey instruments: a brief demographic measure (age, sex, race/ethnicity, marital status, education level, household income level, and employment status), ISI,15 PROMIS (Patient-Reported Outcomes Measurement Information System) Sleep Disturbance and Sleep-Related Impairment scales,16 the 10-item Functional Outcomes of Sleep Questionnaire,17 General Anxiety Disorder 7-Item Scale,18 Perceived Stress Scale,19 and Patient Health Questionnaire 8.20 Participants also completed items from the Consensus Sleep diary.21 Items included bedtime, sleep latency, number of awakenings, total duration of awakenings, final wake time, and rise time. The sleep diary data were cleaned (eg, reviewed for AM/PM errors, negative sleep efficiencies, and sleep efficiencies > 1). Diaries were considered valid if participants had at least 4 valid days completed. Sleep-wake data were estimated using a Charge 5 Fitbit that was worn during the baseline week, the first week of the trial, and the last week of the trial. Fitbits are comparable to research-grade actigraphy for estimating sleep duration.22 A recent study presented analysis of discrepancies between Fitbit, polysomnography, and other consumer sleep devices. Results demonstrated that total sleep time was overestimated by 5.97 minutes, and sleep efficiency was overestimated by 1.16% compared to polysomnography.23 Fitbit data were collected and aggregated using the Fitabase platform. Fitbit-derived sleep variables included total sleep time, wake after sleep onset, and sleep efficiency (percent of time asleep divided by the sleep period time). Sleep periods were autodetected, and therefore, the sleep latency variable was not valid. Sleep variables were generated using the stages algorithm (with heart rate data) when possible, and if not available, using the classic (movement only) algorithm. Most days, both pre baseline and post 4 weeks for each group were scored using the stages algorithm (> 90%), and therefore, all valid days were used in the analysis. To determine a valid day, we first identified the primary sleep period. Primary sleep periods < 2 hours were excluded if the sleep diary did not corroborate the very short sleep period. Fitbit data were considered valid if participants had at least 4 nights of valid data.
Evolv28 adherence
Evolv28 adherence was collected via the company’s dashboard. At 4 weeks and 3 months, participants completed a measure that asked whether they experienced any symptoms while wearing the sleep device, when they developed the symptoms, and their degree of severity. Staff also completed an adverse events log if they were notified of an adverse event.
Data analysis
Data were analyzed using R version 4.2.2 using descriptive statistics and linear mixed models to test the effect for time and time × group interaction. The primary outcome was defined as change in ISI at 1 month. We also conducted linear mixed models to examine change over time and time × group changes from baseline to 3 months. Analyses were conducted as intention to treat, and all participants who completed baseline data and were randomly assigned were included in the mixed models. We utilized chi-square tests to evaluate percentage with a response to the intervention (decrease of 6 points or more on the ISI) and remission (ISI postintervention score ≤ 7).
RESULTS
Sample characteristics
The CONSORT (Consolidated Standards of Reporting Trials) diagram (Figure 1) lists the number of participants at screening, enrollment, and follow-up. A total of 476 participants completed online screening, and 59 participants were enrolled and randomly assigned into the study. Due to a high response rate, the ad only ran for 7 days before we recruited the number of prespecified participants for this study. Participant characteristics are listed in Table 1. Common reasons for participant exclusion included frequent migraines or headaches (16%), too low of an ISI score (14%), other diagnosed sleep disorders (13%), recent hospitalizations (8%), mental health reasons (6%), and other current insomnia treatments (6%). The survey was dynamic in that if participants were excluded for the first reason, they were not able to continue filling out the survey.
Figure 1. CONSORT diagram.
Table 1.
Baseline characteristics.
| Characteristic | Intervention | Control | Full Sample |
|---|---|---|---|
| Age (years) mean (standard deviation) | 38.9 (12.5) | 41.6 (11.8) | 40.4 (12.1) |
| Sex | |||
| Female | 19 (68) | 20 (65) | 39 (66) |
| Male | 9 (32) | 11 (35) | 20 (34) |
| Race | |||
| White | 20 (71) | 22 (71) | 42 (71) |
| Asian | 6 (21) | 4 (13) | 10 (17) |
| Black/African American | 2 (7) | 4 (13) | 6 (10) |
| Native Hawaiian/Pacific Islander | 0 (0) | 1 (3) | 1 (2) |
| Ethnicity | |||
| Hispanic/Latino | 1 (4) | 4 (13) | 5 (8) |
| Non-Hispanic/Latino | 27 (96) | 27 (87) | 54 (92) |
| Employment status | |||
| Full-timea | 13 (46) | 18 (58) | 31 (53) |
| Part-timea | 5 (18) | 6 (18) | 11 (19) |
| Student | 3 (11) | 3 (11) | 6 (10) |
| Not employed | 5 (18) | 3 (10) | 8 (14) |
| Retired | 2 (7) | 1 (4) | 3 (5) |
| Highest level of education | |||
| High school or some high school | 5 (18) | 5 (16) | 10 (17) |
| Associate degree or trade school | 8 (29) | 6 (19) | 14 (24) |
| Bachelor’s degree | 8 (29) | 9 (29) | 17 (29) |
| Graduate degree | 7 (25) | 11 (35) | 18 (31) |
| Combined yearly household income | |||
| $25,000 or below | 3 (11) | 6 (19) | 9 (15) |
| $26,000–$50,000 | 6 (21) | 4 (13) | 10 (17) |
| $51,000–$75,000 | 8 (29) | 6 (19) | 14 (24) |
| $76,000–$100,000 | 4 (14) | 6 (19) | 10 (17) |
| >$100,000 | 6 (21) | 6 (19) | 12 (20) |
| Prefer not to say | 1 (4) | 3 (10) | 4 (7) |
N = 59 (n = 28 for intervention and n = 31 for control). Values are presented as n (%) unless otherwise specified. Participants were on average 40.4 years old (standard deviation = 12.1), and participant age did not differ by condition. aFull-time reflects 32 hours or more of work per week. Part-time reflects less than 32 hours of work per week.
Device adherence
There were no differences in adherence between groups. Most participants were adherent at the recommended 3 hours per day (intervention: 64% ± 29.0, control: 66% ± 35.0), but adherence dropped off in the open-label period (intervention: 7 days ± 16.4, control: 4.7 ± 35.0).
Outcomes at 1 month (Table 2 and Table 3)
Table 2.
Self-reported outcomes at 1 month.
| Assessment | Intervention | Control | Pbetween | Pwithin | ||||
|---|---|---|---|---|---|---|---|---|
| Baseline | 1 month | Change | Baseline | 1 month | Change | |||
| Insomnia Severity Index | 19.1 (3.3) | 11.8 (5.2) | −7.3 (1.9) | 18.6 (3.2) | 11.0 (4.0) | −7.6 (0.84) | .88 | .001 |
| PROMIS Sleep Disturbance | 60.6 (5.9) | 53.8 (7.9) | −6.8 (2.0) | 60.8 (4.9) | 53.5 (4.9) | −7.3 (0.05) | .98 | .001 |
| PROMIS Sleep-Related Impairment | 61.0 (6.1) | 56.0 (8.0) | −5.0 (1.9) | 60.4 (6.2) | 53.4 (8.1) | −7.0 (1.97) | .37 | .001 |
| General anxiety disorder | 7.00 (4.9) | 5.72 (4.6) | −1.3 (0.3) | 6.71 (4.2) | 4.90 (3.5) | −1.8 (0.65) | .53 | .005 |
| Perceived Stress Scale | 16.9 (6.4) | 15.8 (7.6) | −1.1 (1.2) | 16.4 (6.7) | 15.7 (6.2) | −0.7 (0.49) | .87 | .44 |
| Functional Outcomes of Sleep | 32.8 (3.9) | 35.8 (4.9) | 3.1 (1.0) | 31.8 (5.6) | 35.2 (4.7) | 3.4 (0.90) | .81 | .002 |
| Patient Health Questionnaire | 7.40 (3.6) | 5.4 (3.6) | −2.0 (0.1) | 7.7 (3.6) | 4.7 (3.4) | −3.0 (0.23) | .39 | .001 |
Values are mean (standard deviation). Missing questionnaire data n = 3 in the intervention group and n = 2 for the control group. Pbetween = P value for the time × condition effect, Pwithin = P value for the time effect, PROMIS = Patient-Reported Outcomes Measurement Information System.
Table 3.
Fitbit and sleep diary outcomes at 1 month.
| Assessment | Intervention | Control | Pbetween | Pwithin | ||||
|---|---|---|---|---|---|---|---|---|
| Baseline | 1 month | Change | Baseline | 1 month | Change | |||
| Sleep diary | ||||||||
| Sleep duration (hours) | 6.36 (1.77) | 6.89 (2.08) | 0.53 (0.30) | 6.36 (1.5) | 6.64 (1.86) | .28 (0.34) | .25 | .046 |
| WASO (minutes) | 34.8 (53.4) | 28.8 (49.8) | −6.0 (3.39) | 29.3 (44.4) | 31.8 (42.0) | 2.4 (−2.7) | .37 | .73 |
| Efficiency (%) | 75.0 (0.2) | 79.0 (0.2) | 4.0 (0.1) | 78.0 (0.1) | 77.0 (0.2) | −1.0 (0.2) | .03 | .90 |
| Sleep latency (minutes) | 43.2 (46.2) | 39 (42.0) | −4.2 (4.69) | 41.4 (41.4) | 43.2 (52.2) | 1.8 (10.7) | .07 | .63 |
| Fitbit | ||||||||
| Sleep duration (hours) | 6.28 (0.58) | 6.47 (1.02) | 0.19 (0.83) | 6.37 (0.88) | 6.47 (1.45) | 0.1 (1.21) | .80 | .70 |
| WASO (minutes) | 48.8 (8.1) | 51.4 (17.7) | 2.6 (13.7) | 50.9 (17.2) | 49.8 (16.9) | −0.9 (17.1) | .46 | .74 |
| Efficiency (%) | 93.6 (2.6) | 92.9 (5.8) | −0.7 (4.5) | 93.9 (2.4) | 94.1 (2.80) | 0.2 (2.61) | .55 | .81 |
Values are mean (standard deviation). Missing Fitbit data (n = 23), missing data for sleep diaries (n = 5). Pbetween = P value for the time × condition effect, Pwithin = P value for the time effect, WASO = wake after sleep onset.
There was a significant effect for time for most measures, indicating that both groups experienced improvements in insomnia symptoms, sleep quality, anxiety, and depressive symptoms. There was a significant effect for time for sleep-diary-reported sleep duration, indicating improvements in sleep duration among both the intervention and control groups. In addition, there was a significant time × group interaction for diary-reported sleep efficiency, with the intervention group reporting greater improvements at the 1-month follow-up compared to the control group. There were no other significant time × condition effects.
Self-reported outcomes at 3-month follow-up ( Table 4 )
Table 4.
Results of self-reported outcomes at 3 months.
| Assessment | Intervention | Control | Pbetween | Pwithin | ||||
|---|---|---|---|---|---|---|---|---|
| Baseline | 3 months | Change | Baseline | 3 months | Change | |||
| Insomnia Severity Index | 19.1 (3.3) | 11.2 (4.7) | −8.0 (1.36) | 18.6 (3.2) | 9.3 (4.5) | −9.3 (1.3) | .36 | .001 |
| PROMIS Sleep Disturbance | 60.6 (5.9) | 53.7 (8.0) | −6.8 (2.2) | 60.8 (4.9) | 52.4 (6.5) | −8.4 (1.7) | .48 | .001 |
| PROMIS Sleep- Related Impairment | 61.0 (6.1) | 56.2 (9.4) | −4.8 (3.3) | 60.4 (6.2) | 52.6 (9.1) | −7.8 (2.9) | .25 | .001 |
| General anxiety disorder | 7.0 (4.9) | 7.24 (5.6) | 0.2 (5.1) | 6.7 (4.2) | 5.1 (5.4) | −1.6 (5.8) | .28 | .34 |
| Perceived Stress Scale | 16.9 (6.4) | 17.5 (7.6) | 0.6 (1.2) | 16.4 (6.7) | 15.0 (7.8) | −1.4 (1.1) | .25 | .22 |
| Functional Outcomes of Sleep | 32.8 (3.9) | 34.6 (5.9) | 1.8 (2.1) | 31.8 (5.6) | 35.2 (5.4) | 3.4 (0.1) | .32 | .004 |
| Patient Health Questionnaire | 7.4 (3.6) | 7.1 (4.8) | −0.3 (1.2) | 7.6 (3.6) | 5.4 (4.7) | −2.2 (1.01) | .11 | .007 |
Values are mean (standard deviation). Missing data n = 1 at the 3-month assessment. Pbetween = P value for the time × condition effect, Pwithin = P value for the time effect, PROMIS = Patient-Reported Outcomes Measurement Information System.
There was a significant change over time for most of the self-report measures, including insomnia symptoms, sleep quality, anxiety, and depression. There were no significant differences between the intervention and control groups for any of the self-reported measures.
Response and remission
There were no differences between groups for response or remission on the ISI. Over half (55%) of participants in the control group and 68% of participants in the intervention group met criteria for a response on the ISI (decrease of 6 points or more). In addition, a similar percentage of participants in each group met criteria for remission on the ISI (ISI postintervention score ≤ 7, 24% of participants in the control group and 20% of participants in the intervention group).
Adverse events
A total of 4 adverse events were reported: 3 participants in the control group reported mild headaches (1 discontinued the intervention), and 1 participant in the intervention group reported severe nerve pain from the device pinching their neck and discontinued participation. All reported adverse events were reported within the first 10 days of the trial, and events resolved when they stopped using the device.
DISCUSSION
The current study tested the efficacy of a wearable device that uses VCMFs compared to a sham device among participants with moderate to severe insomnia symptoms. Results demonstrated that participants were eager to try this treatment, and adherence to the intervention wear time of 3 hours per day was high. However, for most measures, there were improvements in both the intervention and control conditions. The intervention group improved in diary-based sleep efficiency, which may be a distinction between groups because diary-based sleep efficiency is a primary clinical outcome in most clinical trials of insomnia treatments.24 It is also important to point out that the magnitude of change in self-reported insomnia symptoms and sleep-diary-based sleep duration in both groups was as large as or larger than cognitive behavioral therapy for insomnia.25
A key feature of our study is that the design utilized a very rigorous placebo, in which participants wore the same device as the intervention condition, but with nontherapeutic frequencies. Participants were unable to determine which device they were wearing, because the stimulation was not perceptible. A powerful placebo effect is well known in insomnia treatments.26 For example, a meta-analysis found that although repetitive transcranial magnetic stimulation was shown to improve sleep, it was estimated that 73% of the benefits were due to placebo.27 In addition, a study that compared a 12-session neurofeedback intervention to a sham neurofeedback control also observed improvements in self-reported sleep among both groups.28 These results point to a powerful effect of using a device on insomnia symptoms, but the changes in sleep are largely related to nonspecific factors.
This study adds to the small but growing literature examining wearable devices for sleep problems. Although this study did not do a comprehensive search, based on our literature and internet search for wearable sleep devices, we found that previous studies have examined wearable electroencephalogram sensors,29 cranial electrical stimulation,30 and electrical stimulation behind the ears.31 One other study tested a similar device using ultra-low magnetic waves delivered in a neckband,32 but results are presented on the company’s website and not in a peer-reviewed publication. Therefore, there is a significant need to conduct further independent testing of wearable devices using randomized design.
Limitations of our study include a small sample size that was designed to observe a moderate to large effect size, and the 3-month follow-up was relatively short. Strengths of the study include the use of a double-blinded placebo-controlled design, objective and self-report measures, and rigorous placebo. It is also possible that 3 hours per day was too low of a dose, and it is unknown whether a longer wear time may have impacted results. In summary, this study demonstrates that technology-based treatments are highly desired by patients with insomnia and should be explored further in future research.
DISCLOSURE STATEMENT
All authors have seen and approved the manuscript. Work for this study was performed at the University of Utah. This project was funded by Aether Mindtech, the parent company of the Evolv28 device. Aether Mindtech was not involved in the conduct of the study or presentation of the results. All authors report the presence of financial support and no conflicts of interest.
ACKNOWLEDGMENTS
The authors thank Brian Baucom, PhD, for overseeing the statistical analyses in this article.
ABBREVIATIONS
- ISI
Insomnia Severity Index
- VCMFs
variable complex weak magnetic fields
EDITOR’S NOTE
The Emerging Technologies section focuses on new tools and techniques of potential utility in the diagnosis and management of any and all sleep disorders. The technologies may not yet be marketed, and indeed may only exist in prototype form. Some preliminary evidence of efficacy must be available, which can consist of small pilot studies or even data from animal studies, but definitive evidence of efficacy will not be required, and the submissions will be reviewed according to this standard. The intent is to alert readers of Journal of Clinical Sleep Medicine of promising technology that is in early stages of development. With this information, the reader may wish to (1) contact the author(s) in order to offer assistance in more definitive studies of the technology; (2) use the ideas underlying the technology to develop novel approaches of their own (with due respect for any patent issues); and (3) focus on subsequent publications involving the technology in order to determine when and if it is suitable for application to their own clinical practice. The Journal of Clinical Sleep Medicine and the American Academy of Sleep Medicine expressly do not endorse or represent that any of the technology described in the Emerging Technologies section has proven efficacy or effectiveness in the treatment of human disease, nor that any required regulatory approval has been obtained.
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