frequency range Search Results


90
MISTRAS Group Inc eight pico ae sensors (the operating frequency ranges between 200 and 750 khz, with a resonant frequency of ~ 500 khz)
Eight Pico Ae Sensors (The Operating Frequency Ranges Between 200 And 750 Khz, With A Resonant Frequency Of ~ 500 Khz), supplied by MISTRAS Group Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/eight pico ae sensors (the operating frequency ranges between 200 and 750 khz, with a resonant frequency of ~ 500 khz)/product/MISTRAS Group Inc
Average 90 stars, based on 1 article reviews
eight pico ae sensors (the operating frequency ranges between 200 and 750 khz, with a resonant frequency of ~ 500 khz) - by Bioz Stars, 2026-06
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90
PCB Piezotronics ultrasonic microphones with a frequency detection range of 10–100 khz
Ultrasonic Microphones With A Frequency Detection Range Of 10–100 Khz, supplied by PCB Piezotronics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/ultrasonic microphones with a frequency detection range of 10–100 khz/product/PCB Piezotronics
Average 90 stars, based on 1 article reviews
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IEEE Access periodic fixed-frequency staggered line leaky wave antenna with wide-range beam scanning capacity
Periodic Fixed Frequency Staggered Line Leaky Wave Antenna With Wide Range Beam Scanning Capacity, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/periodic fixed-frequency staggered line leaky wave antenna with wide-range beam scanning capacity/product/IEEE Access
Average 90 stars, based on 1 article reviews
periodic fixed-frequency staggered line leaky wave antenna with wide-range beam scanning capacity - by Bioz Stars, 2026-06
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90
COMSOL Inc total sound pressure field with the frequency range of 200 khz to 2 mhz
Total Sound Pressure Field With The Frequency Range Of 200 Khz To 2 Mhz, supplied by COMSOL Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/total sound pressure field with the frequency range of 200 khz to 2 mhz/product/COMSOL Inc
Average 90 stars, based on 1 article reviews
total sound pressure field with the frequency range of 200 khz to 2 mhz - by Bioz Stars, 2026-06
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90
Siemens AG vf10e5 linear transducer (5e10 mhz frequency range)
Vf10e5 Linear Transducer (5e10 Mhz Frequency Range), supplied by Siemens AG, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/vf10e5 linear transducer (5e10 mhz frequency range)/product/Siemens AG
Average 90 stars, based on 1 article reviews
vf10e5 linear transducer (5e10 mhz frequency range) - by Bioz Stars, 2026-06
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90
Cambridge SoundWorks small, wide frequency range speaker
Small, Wide Frequency Range Speaker, supplied by Cambridge SoundWorks, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/small, wide frequency range speaker/product/Cambridge SoundWorks
Average 90 stars, based on 1 article reviews
small, wide frequency range speaker - by Bioz Stars, 2026-06
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Verum Diagnostica GmbH slow wave activity in the low-frequency range of 0.75–1.25 hz (lowswa)
a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of <t>lowSWA</t> for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) <t>during</t> <t>Verum.</t> Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .
Slow Wave Activity In The Low Frequency Range Of 0.75–1.25 Hz (Lowswa), supplied by Verum Diagnostica GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/slow wave activity in the low-frequency range of 0.75–1.25 hz (lowswa)/product/Verum Diagnostica GmbH
Average 90 stars, based on 1 article reviews
slow wave activity in the low-frequency range of 0.75–1.25 hz (lowswa) - by Bioz Stars, 2026-06
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90
Tektronix inc wide frequency range generator
a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of <t>lowSWA</t> for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) <t>during</t> <t>Verum.</t> Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .
Wide Frequency Range Generator, supplied by Tektronix inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/wide frequency range generator/product/Tektronix inc
Average 90 stars, based on 1 article reviews
wide frequency range generator - by Bioz Stars, 2026-06
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90
TOSHIBA Medical plt-705bt probe (a linear probe with a frequency range of 3-11 mhz)
a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of <t>lowSWA</t> for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) <t>during</t> <t>Verum.</t> Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .
Plt 705bt Probe (A Linear Probe With A Frequency Range Of 3 11 Mhz), supplied by TOSHIBA Medical, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/plt-705bt probe (a linear probe with a frequency range of 3-11 mhz)/product/TOSHIBA Medical
Average 90 stars, based on 1 article reviews
plt-705bt probe (a linear probe with a frequency range of 3-11 mhz) - by Bioz Stars, 2026-06
90/100 stars
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90
Canon inc linear array transducer 5 18 mhz frequency range
a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of <t>lowSWA</t> for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) <t>during</t> <t>Verum.</t> Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .
Linear Array Transducer 5 18 Mhz Frequency Range, supplied by Canon inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/linear array transducer 5 18 mhz frequency range/product/Canon inc
Average 90 stars, based on 1 article reviews
linear array transducer 5 18 mhz frequency range - by Bioz Stars, 2026-06
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90
Pacific Scientific gauss meter with a frequency range of 20 hz to 2000 hz
a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of <t>lowSWA</t> for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) <t>during</t> <t>Verum.</t> Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .
Gauss Meter With A Frequency Range Of 20 Hz To 2000 Hz, supplied by Pacific Scientific, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/gauss meter with a frequency range of 20 hz to 2000 hz/product/Pacific Scientific
Average 90 stars, based on 1 article reviews
gauss meter with a frequency range of 20 hz to 2000 hz - by Bioz Stars, 2026-06
90/100 stars
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90
Siemens AG acusion sequoia 5c1 transducer (frequency: 5 mhz, range: 1.4-5.0 mhz, field of view: 70°)
a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of <t>lowSWA</t> for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) <t>during</t> <t>Verum.</t> Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .
Acusion Sequoia 5c1 Transducer (Frequency: 5 Mhz, Range: 1.4 5.0 Mhz, Field Of View: 70°), supplied by Siemens AG, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/acusion sequoia 5c1 transducer (frequency: 5 mhz, range: 1.4-5.0 mhz, field of view: 70°)/product/Siemens AG
Average 90 stars, based on 1 article reviews
acusion sequoia 5c1 transducer (frequency: 5 mhz, range: 1.4-5.0 mhz, field of view: 70°) - by Bioz Stars, 2026-06
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Image Search Results


a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of lowSWA for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) during Verum. Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .

Journal: Communications Medicine

Article Title: Auditory deep sleep stimulation in older adults at home: a randomized crossover trial

doi: 10.1038/s43856-022-00096-6

Figure Lengend Snippet: a Individual (all nights of n subjects = 16) ON-OFF difference (calculated using ON-OFF analysis, see methods) of lowSWA for all windows with >2 stimulations sorted by averaged lowSWA (red horizontal lines) during Verum. Strong responders refer to the upper 50% and weak responders to the lower 50% of participants. Clear ON-OFF differences during Verum condition across the majority of nights are seen for strong responders but not that clearly for weak responders. (S = Sham, V = Verum). b Linear discrimination analysis (LDA) using 10-fold cross-validation. All good quality nights during Verum ONOFF were included in the model and labeled as weak or strong responder night (dependent variable for classification). For lowSWA and %NREM N3 (non-rapid eye movement stage 3) during baseline, number of stimulations during NREM sleep and mean sound volume (prediction factors) a separate LDA model was run and accuracy in predicting weak and strong responder nights were plotted in blue. * indicate p < 0.05 comparing accuracy achieved by the prediction factors to chance level (No Information Rate). c Comparison of lowSWA ON-OFF difference between weak and strong responder (factor resp) for windows that only included sound volume at 52 dB (baseline lowest level) and for different stimulation bins (factor stim#) using a robust linear mixed-effect model (LMM) illustrated as error bars (mean ± SEM) with data points representing individual participants. The y -axis has been condensed to better visualize the error bars despite outliers. d – f Repeated measures (rm) correlations to investigate the prediction of nightly lowSWA ON-OFF difference variance. d Predictor baseline lowSWA for all good quality Verum ONOFF nights. e Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights. f Predictor number of NREM sleep stimuli for all good quality Verum ONOFF nights in strong responder subjects. Data underlying this figure is provided in Supplementary Data .

Article Snippet: Repeated measures (rm) correlation of ( a ) slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) (calculated using the consecutive analysis (see methods), windows with >2 stimulations) changes in Verum relative to Sham and ( b ) REM sleep changes relative to Sham with mood changes relative to Sham.

Techniques: Biomarker Discovery, Labeling, Comparison

Repeated measures (rm) correlation of ( a ) slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) (calculated using the consecutive analysis (see methods), windows with >2 stimulations) changes in Verum relative to Sham and ( b ) REM sleep changes relative to Sham with mood changes relative to Sham. Mood assessments were used from the morning assessments (lower values indicate a more negative mood). All nights during Verum were taken (pooled approaches in this correlation) relative to the averaged values of the respective Sham period (Sham ONOFF in windowed Verum nights, Sham ON in continuous Verum nights). Data underlying this figure is provided in Supplementary Data .

Journal: Communications Medicine

Article Title: Auditory deep sleep stimulation in older adults at home: a randomized crossover trial

doi: 10.1038/s43856-022-00096-6

Figure Lengend Snippet: Repeated measures (rm) correlation of ( a ) slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) (calculated using the consecutive analysis (see methods), windows with >2 stimulations) changes in Verum relative to Sham and ( b ) REM sleep changes relative to Sham with mood changes relative to Sham. Mood assessments were used from the morning assessments (lower values indicate a more negative mood). All nights during Verum were taken (pooled approaches in this correlation) relative to the averaged values of the respective Sham period (Sham ONOFF in windowed Verum nights, Sham ON in continuous Verum nights). Data underlying this figure is provided in Supplementary Data .

Article Snippet: Repeated measures (rm) correlation of ( a ) slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) (calculated using the consecutive analysis (see methods), windows with >2 stimulations) changes in Verum relative to Sham and ( b ) REM sleep changes relative to Sham with mood changes relative to Sham.

Techniques: Activity Assay

a Ratio (mean, shaded area SEM) between Verum and Sham of the normalized spectral density (power divided by cumulative EEG power up to 30 Hz) during non-rapid eye movement (NREM) sleep (device and offline detected) shows a significant cluster of frequency bins in the low-frequency range of 1–1.25 Hz. P -values (fixed factor condition) were derived from a robust LMM (see methods) performed for each frequency bin separately. b Slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) in windows containing more than 2 stimulations for Sham and Verum, for weak and strong responders separately illustrated as error bars (mean ± SEM) with data points representing individual participants. Robust linear mixed model results comparing conditions (factor cond) and the interaction of the condition (Verum vs Sham) and responder (factor resp, weak vs strong) are depicted in the gray panel. c LowSWA summed overall device and offline detected NREM sleep periods (energy, lowSWE) for Verum ON (continuous approach) Verum ONOFF (windowed approach), for weak and strong responders separately illustrated as error bars (mean ± SEM) with data points representing individual participants. Overall robust LMM results (all night included in model) regarding approach (appr) and the interaction of approach and responder are summarized in the gray panel. d LowSWA in windows containing more than 2 stimulations comparing windowed and continuous approaches in responders ( n subjects = 7), for Verum and Sham separately illustrated as error bars (mean ± SEM) with data points representing individual participants. Robust LMM comparing approaches (continuous vs windowed) are summarized in the gray panel. Data underlying this figure is provided in Supplementary Data .

Journal: Communications Medicine

Article Title: Auditory deep sleep stimulation in older adults at home: a randomized crossover trial

doi: 10.1038/s43856-022-00096-6

Figure Lengend Snippet: a Ratio (mean, shaded area SEM) between Verum and Sham of the normalized spectral density (power divided by cumulative EEG power up to 30 Hz) during non-rapid eye movement (NREM) sleep (device and offline detected) shows a significant cluster of frequency bins in the low-frequency range of 1–1.25 Hz. P -values (fixed factor condition) were derived from a robust LMM (see methods) performed for each frequency bin separately. b Slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) in windows containing more than 2 stimulations for Sham and Verum, for weak and strong responders separately illustrated as error bars (mean ± SEM) with data points representing individual participants. Robust linear mixed model results comparing conditions (factor cond) and the interaction of the condition (Verum vs Sham) and responder (factor resp, weak vs strong) are depicted in the gray panel. c LowSWA summed overall device and offline detected NREM sleep periods (energy, lowSWE) for Verum ON (continuous approach) Verum ONOFF (windowed approach), for weak and strong responders separately illustrated as error bars (mean ± SEM) with data points representing individual participants. Overall robust LMM results (all night included in model) regarding approach (appr) and the interaction of approach and responder are summarized in the gray panel. d LowSWA in windows containing more than 2 stimulations comparing windowed and continuous approaches in responders ( n subjects = 7), for Verum and Sham separately illustrated as error bars (mean ± SEM) with data points representing individual participants. Robust LMM comparing approaches (continuous vs windowed) are summarized in the gray panel. Data underlying this figure is provided in Supplementary Data .

Article Snippet: Repeated measures (rm) correlation of ( a ) slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) (calculated using the consecutive analysis (see methods), windows with >2 stimulations) changes in Verum relative to Sham and ( b ) REM sleep changes relative to Sham with mood changes relative to Sham.

Techniques: Derivative Assay, Activity Assay

a Ratio (mean, shaded area SEM) between Verum and Sham in the windowed approach of the normalized spectral density (power divided by cumulative electroencephalography [EEG] power up to 30 Hz) during non-rapid eye movement (NREM) sleep (device and offline detected, consecutive analysis see methods) shows a significant cluster of frequency bins in the low-frequency range of 0.75–1.25 Hz (lowSWA). P -values (fixed factor condition, cond) were derived from a robust linear mixed model (see methods) performed for each frequency bin separately. b Error bars (mean ± SEM) with data points representing individual participants of ON-OFF window analysis of lowSWA for the difference between ON-OFF, ON windows, and OFF windows (see methods). Windows with stimulations (triggers or tones) were sorted and matched for their number of stimulations (stim#, 1–2 stimulations (1–2 stim), 3–4 stimulations (3–4 stim), and more than 4 stimulations (>4 stim)) and compared between Verum and Sham condition. Overall robust linear mixed model results (model includes average of nights) are summarized in the gray panels. The y-axis has been condensed to better visualize the error bars despite outliers. In case of significant main or interaction effects, a robust linear mixed-effects model was calculated for each stimulation bin separately (robust linear mixed-effect model [LMM], model includes all nights, *indicate p < 0.05 **indicate p < 0.01, stars in brackets illustrate exploratory analysis because of non-significant interaction effect). Effect of ON-OFF difference is driven by a significant increase of lowSWA in the ON window as indicated by a significant main effect of condition in a robustLMM, but not the OFF window. Following this significant overall model, separate robust LMM including all nights depict that specifically stimulation bins with more than 2 stimulations (3–4 stim, >4stim) show a significant condition effect in the ON window (*indicate p < 0.05). c In an additional analysis of all the ON-OFF window differences with more than 2 stims, we focused on whether there is a consistent difference between Verum and Sham for all seven nights. Results are shown as error bars (mean ± SEM) and data points represent individual nights of 16 participants. The y -axis has been condensed to better visualize the error bars despite outliers. In a robust LMM with factors nights, conditions, and control fixed and random factors (see methods) revealed no significant interaction night x condition ( p > 0.1) and a main effect condition ( p < 0.001), indicating a significant effect between Sham and Verum across all seven nights. Solid lines refer to ON window results, long dashed lines to ON-OFF difference and short dashed lines to OFF window results. Data underlying this figure is provided in Supplementary Data .

Journal: Communications Medicine

Article Title: Auditory deep sleep stimulation in older adults at home: a randomized crossover trial

doi: 10.1038/s43856-022-00096-6

Figure Lengend Snippet: a Ratio (mean, shaded area SEM) between Verum and Sham in the windowed approach of the normalized spectral density (power divided by cumulative electroencephalography [EEG] power up to 30 Hz) during non-rapid eye movement (NREM) sleep (device and offline detected, consecutive analysis see methods) shows a significant cluster of frequency bins in the low-frequency range of 0.75–1.25 Hz (lowSWA). P -values (fixed factor condition, cond) were derived from a robust linear mixed model (see methods) performed for each frequency bin separately. b Error bars (mean ± SEM) with data points representing individual participants of ON-OFF window analysis of lowSWA for the difference between ON-OFF, ON windows, and OFF windows (see methods). Windows with stimulations (triggers or tones) were sorted and matched for their number of stimulations (stim#, 1–2 stimulations (1–2 stim), 3–4 stimulations (3–4 stim), and more than 4 stimulations (>4 stim)) and compared between Verum and Sham condition. Overall robust linear mixed model results (model includes average of nights) are summarized in the gray panels. The y-axis has been condensed to better visualize the error bars despite outliers. In case of significant main or interaction effects, a robust linear mixed-effects model was calculated for each stimulation bin separately (robust linear mixed-effect model [LMM], model includes all nights, *indicate p < 0.05 **indicate p < 0.01, stars in brackets illustrate exploratory analysis because of non-significant interaction effect). Effect of ON-OFF difference is driven by a significant increase of lowSWA in the ON window as indicated by a significant main effect of condition in a robustLMM, but not the OFF window. Following this significant overall model, separate robust LMM including all nights depict that specifically stimulation bins with more than 2 stimulations (3–4 stim, >4stim) show a significant condition effect in the ON window (*indicate p < 0.05). c In an additional analysis of all the ON-OFF window differences with more than 2 stims, we focused on whether there is a consistent difference between Verum and Sham for all seven nights. Results are shown as error bars (mean ± SEM) and data points represent individual nights of 16 participants. The y -axis has been condensed to better visualize the error bars despite outliers. In a robust LMM with factors nights, conditions, and control fixed and random factors (see methods) revealed no significant interaction night x condition ( p > 0.1) and a main effect condition ( p < 0.001), indicating a significant effect between Sham and Verum across all seven nights. Solid lines refer to ON window results, long dashed lines to ON-OFF difference and short dashed lines to OFF window results. Data underlying this figure is provided in Supplementary Data .

Article Snippet: Repeated measures (rm) correlation of ( a ) slow wave activity in the low-frequency range of 0.75–1.25 Hz (lowSWA) (calculated using the consecutive analysis (see methods), windows with >2 stimulations) changes in Verum relative to Sham and ( b ) REM sleep changes relative to Sham with mood changes relative to Sham.

Techniques: Derivative Assay, Control