Contact-free ballistocardiography for remote screening

Emfit’s QS+CLINICAL™ hardware is a registered medical device in EU for the purpose of without-patient-contact transforming movement from a body, breathing and heart contractions into electrical signal.

Emfit joined the renaissance of ballistocardiography already in early 1990’s. The first scientific publication was published in 1993.

QS+CLINICAL can record, transfer and store the signal data for the purpose of investigating physiological processes at rest. The collected signal data are intended for healthcare professionals to decide if further tests are needed to diagnose as example obstructive or central sleep apnea or atrial fibrillation. 

Emfit’s sensors have been widely used in scientific research of ballistocardiography. Today there are close to 100 scientific publications in total. QS+CLINICAL makes it possible to conduct investigation easily and conveniently for patients, and collect data remotely over the Internet.

Contact-free remote screening

QS+CLINICAL™ is a ballistocardiography* sensor that records heart contractions, breathing and body movement bio-signals. It connects wirelessly over the Internet to the Emfit's SleepCore® software solution for data storage and visualization with web application. Waveform files are also available for download in .edf format.

* Ballistocardiography, a technique for sensing the sudden ejection of blood into the great vessels with each heart beat, and breathing movement analysis.

What makes Emfit sensor so good for apnea screening?

The core of the company’s patented sensor technology is also the key to its ability to produce such a clean band-pass filtered waveform without any alterations caused by the electroactive material used.

While competitive materials, such as PZT or PVDF used by competition, are crystalline and harsh, the Emfit’s proprietary sensor material is designed to be soft and cellular to avoid any resonance within the material itself. Therefore there is no “ringing,” which almost entirely eliminates cross talk from other sleeper in bed and is often a problem with piezo materials. Importantly also for data procesing, for example, when atriums and ventriculars of the heart contract, the produced signal is exact and purestly clean which is needed for accurate heart rate variability calculation. This also makes the sensor signal visualisation so clear for clinicians and researchers who are interested in using it to investigate heart and breathing issues.

“Time percentage with all obstructive periodic Emfit breathing patterns (OPTotal%) showed the best correlation with the AHI. The OPTotal percentage of 21 yielded to excellent accuracy in detecting subjects with an AHI of 15/h or more. Patients with IRR received high scores in GHQ-12-questionnaire.”

Excerpt from: Emfit movement sensor in evaluating nocturnal breathing

Mirja Tenhunen, Ella Elomaa, Heli Sistonen, Esa Rauhala, Sari-Leena Himanen

Respiratory Physiology & Neurobiology 187 (2013) 183– 189

Emfit® in scientific publications

Emfit movement sensor in evaluating nocturnal breathing

Mirja Tenhunen, Ella Elomaa, Heli Sistonen, Esa Rauhala, Sari-Leena Himanen

Respiratory Physiology & Neurobiology 187 (2013) 183– 189

Abstract: Obstructive sleep apnea (OSA) diagnostics by the movement sensors static charge-sensitive bed (SCSB) and electromechanical film transducer (Emfit) is based on dividing the signal into different breathing patterns. The usage of non-invasive mattress sensors in diagnosing OSA is particularly tempting if patient has many other non sleep-related monitoring sensors. However, a systematic comparison of the apnea–hypopnea index (AHI) with Emfit-parameters is lacking. In addition to periodic breathing, SCSB and Emfit visualize episodes of sustained negative increases in intrathoracic pressure (increased respiratory resistance, IRR), of which relevance is still ambiguous. Our aim is to compare Emfit-parameters with the AHI and to provide a description of the patients suffering from IRR. Time percentage with all obstructive periodic Emfit breathing patterns (OPTotal%) showed the best correlation with the AHI. The OPTotal percentage of 21 yielded to excellent accuracy in detecting subjects with an AHI of 15/h or more. Patients with IRR received high scores in GHQ-12-questionnaire. An Emfit movement sensor might offer additional information in OSA diagnostics especially if nasal pressure transducer cannot be used.

© 2013 Elsevier B.V.

Increased respiratory effort during sleep is non-invasively detected with movement sensor

Mirja Tenhunen, Esa Rauhala, Jussi Virkkala, Olli Polo, Antti Saastamoinen, Sari-Leena Himanen

Sleep Breath (2011) 15:737–746

Abstract: Introduction Measuring breathing effort during sleep with an oesophageal pressure sensor remains technically challenging and has not become routine practice. The aim of the present work was to investigate whether increased thoracic pressure during sleep can be detected with the Emfit movement sensor. Experimental data suggest that increased respiratory efforts with the intrathoracic pressure variation induce high-frequency spikes in the Emfit signal, but this has not been systematically examined.

© Springer-Verlag 2010

Screening sleep disordered breathing in stroke unit

Väyrynen K, Kortelainen K, Numminen H, Miettinen K, Keso A, Tenhunen M, Huhtala H, Himanen SL.

Sleep Disord. 2014;2014:317615. doi: 10.1155/2014/317615. Epub 2014 May 27.

PMID: 24991437

Abstract: In acute stroke, OSA has been found to impair rehabilitation and increase mortality but the effect of central apnea is more unclear. The aim of the present study was to evaluate the feasibility of using limited ambulatory recording system (sleep mattress to evaluate nocturnal breathing and EOG-electrodes for sleep staging) in sleep disordered breathing (SDB) diagnostics in mild acute cerebral ischemia patients and to discover the prevalence of various SDB-patterns among these patients. 42 patients with mild ischemic stroke or transient ischemic attack were studied. OSA was found in 22 patients (52.4%). Central apnea was found in two patients (4.8%) and sustained partial obstruction in only one patient (2.4%). Sleep staging with EOG-electrodes only yielded a similar outcome as scoring with standard rules. OSA was found to be common even after mild stroke. Its early diagnosis and treatment would be favourable in order to improve recovery and reduce mortality. Our results suggest that OSA can be assessed by a limited recording setting with EOG-electrodes, sleep mattress, and pulse oximetry.

© 2014 Kirsi Väyrynen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Heart rate variability evaluation of Emfit sleep mattress breathing categories in NREM sleep

Mirja Tenhunen, Jari Hyttinen, Jukka A. Lipponen, Jussi Virkkala, Sonja Kuusimäki, Mika P. Tarvainen, Pasi A. Karjalainen, Sari-Leena Himanen

Clinical Neurophysiology 126 (2015) 967–974

Published: 6 September 2014

Abstract: Objective: Heart rate variability (HRV) analysis of obstructive sleep apnea patients reveals an increase in sympathetic activity. Sleep disordered breathing (SDB) can be also assessed with sleep mattress sensors, as the Emfit sensor, by dividing the signal into different breathing categories. In addition to normal breathing (NB) and periodic apneas/hypopneas (POB), the sleep mattress unveils a breathing category consisting of sustained partial obstruction (increased respiratory resistance, IRR). The aim of our study was to evaluate HRV during these three breathing categories in NREM sleep. Methods: 53 patients with suspected SDB underwent an overnight polysomnography with an Emfit mattress.

The Emfit signal was scored in 3-min epochs according to the established rules. The NB, POB, and IRR epochs were combined to as long NB, POB and IRR periods as possible and HRV was calculated from at least 6-min epochs.

Results: The meanHR did not differ between the breathing categories. HRV parameters revealed an increase in sympathetic activity during POB. The mean LF/HF ratio was highest during POB (3.0) and lowest during IRR (1.3). During NB it was 1.7 (all p-values 6 0.001). Interestingly sympathetic activity decreased and parasympathetic activity increased during IRR as compared to NB (the mean HF power was 1113.8 ms2 during IRR and 928.4 ms2 during NB).

Conclusions: The HRV findings during POB resembled HRV results of sleep apnea patients but during sustained prolonged partial obstruction a shift towards parasympathetic activity was achieved.

Significance: The findings encourage the use of sleep mattresses in SDB diagnostics. In addition the findings suggest that sustained partial obstruction represents its own SDB entity.

 2014 International Federation of Clinical Neurophysiology. 

© Elsevier Ireland Ltd. 

Prolonged spiking in the Emfit sensor in patients with sleep-disordered breathing is characterized by increase in transcutaneous carbon dioxide

E Rauhala, S-L Himanen, A Saastamoinen and O Polo

Physiol. Meas. 28 (2007) 1163–1173 

Abstract: A phenomenon of prolonged spiking in movement sensors, such as staticcharge- sensitive bed or Emfit (electromechanical film) sensors, has been connected to an increase in carbon dioxide tension in wakefulness. Spiking is also a common finding in sleep studies. This made us hypothesize that carbon dioxide changes might also happen in sleep during prolonged spiking episodes in Emfit sheet. We examined four different kinds of breathing pattern episodes: normal breathing, episodes of repetitive apnea, episodes of repetitive hypopnea and episodes with prolonged spiking lasting at least 3 min. One hundred and fifteen episodes from 19 polysomnograms were finally admitted to the study according to the protocol. The changes in the transcutaneous carbon dioxide tension (TcCO2) were defined for different breathing patterns. During prolonged spiking episodes the TcCO2 increased significantly and differed statistically from theTcCO2 changes of normal breathing and periodic breathing patterns (episodes of apnea and hypopnea). The rise in TcCO2 during prolonged spiking episodes might suggest that prolonged spiking is representing another type of breathing disturbance during sleep differing from periodic breathing patterns. The Emfit sensor as a small, flexible and non-invasive sensor might provide useful additional information about breathing during sleep.

© 2007 IOP Publishing Ltd

Detection and Assessment of Sleep-Disordered Breathing with Special Interest of Prolonged Partial Obstruction

Mirja Tenhunen

Doctoral Thesis, Faculty of Medicine of the University of Tampere, 2015.

Abstract: Sleep-disordered breathing (SDB) has become more common and puts more strain on public health services than ever before. Obstructive sleep apnea (OSA) and its health consequences such as different cardiovascular diseases are nowadays well recognized. In addition to OSA, attention has recently been paid to another SDB; prolonged partial obstruction. However, it is often undiagnosed and easily left untreated because of the low number of respiratory events during polysomnography recording. This patient group has found to present with more atypical subjective symptoms than OSA patients. Polysomnography (PSG) is considered to be the gold standard in reference methods in SDB diagnostics. PSG is a demanding and laborious multichannel recording method and often requires subjects to spend one night in a sleep laboratory. There is long tradition in Finland to use mattress sensors in SDB diagnostics. Recently, smaller electromechanical film transducer (Emfit) mattresses have replaced the old Static Charge-Sensitive Bed (SCSB) mattresses. However, a proper clinical validation of Emfit mattresses in SDB diagnostics has not been carried out. In this work, the use of Emfit recording in the detection of sleep apneas, hypopneas, and prolonged partial obstruction with increased respiratory effort was evaluated. The general aim of the thesis is to develop and improve the diagnostic methods for sleep-related breathing disorders. 

© Tampere University of Technology, 2015

Prolonged partial upper airway obstruction during sleep – an underdiagnosed phenotype of sleep-disordered breathing 

Ulla Anttalainen, Mirja Tenhunen, Ville Rimpilä, Olli Polo, Esa Rauhala, Sari-Leena Himanen and Tarja Saaresranta 

Published: 6 September 2016


Abstract: Obstructive sleep apnea syndrome (OSAS) is a well-recognized disorder conventionally diagnosed with an elevated apnea hypopnea index. Prolonged partial upper airway obstruction is a common phenotype of sleep-disordered breathing (SDB), which however is still largely underreported. The major reasons for this are that cyclic breathing pattern coupled with arousals and arterial oxyhemoglobin saturation are easy to detect and considered more important than prolonged episodes of increased respiratory effort with increased levels of carbon dioxide in the absence of cycling breathing pattern and repetitive arousals. There is also a growing body of evidence that prolonged partial obstruction is a clinically significant form of SDB, which is associated with symptoms and co-morbidities which may partially differ from those associated with OSAS. Partial upper airway obstruction is most prevalent in women, and it is treatable with the nasal continuous positive pressure device with good adherence to therapy. This review describes the characteristics of prolonged partial upper airway obstruction during sleep in terms of diagnostics, pathophysiology, clinical presentation, and comorbidity to improve recognition of this phenotype and its timely and appropriate treatment.

© Ulla Anttalainen et al. This is an Open Access article distributed under the terms of the CreativeCommonsAttribution 4.0 International License

Prolonged spiking periods pattern detection method by using Emfit and SCSB signals

Jarmo Alametsä, Antti Saastamoinen, Eero Huupponen, Alpo Värri, Atte Joutsen, Joel Hasan, Esa Rauhala, and Sari-Leena Himanen

Proceedings of the 12th Finnish Artificial Intelligence Conference STeP. 2006.

Abstract: In this work the previously developed spiking detection method [1] was improved in order to compose prolonged spiking periods by post-processing detected spiking events caused by increased respiratory resistance (IRR) from ballistocardiographic (BCG) data, which was recorded with Electromechanical Film (EMFit) sensor and Static Charge Sensitive Bed (SCSB) mattress. In spiking episode, the systolic BCG wave complexes increase in amplitude during IRR.

The SCSB mattress has been used earlier in sleep research for simultaneous recordings of respiration, BCG and movements in order to detect different sleep disorders like apneas and for sleep scoring. Nowadays also the EMFit sheet has shown its usefulness in sleep study.

For this study eleven recordings from different apnea patients were made with SCSB mattress and EMFit sensor in order to detect prolonged spiking episodes of the formerly developed spiking detection method and as a preliminary work to study the amplitude levels from spiking and non-spiking areas of the recorded signals. Adaptable amplitude levels from recorded signals were used for spiking detection and amplitude levels multiplied by 100 times 1.8 were used for artefact rejection. Two variations from formerly presented 10 different variations of the algorithm were chosen and the detected spiking seconds were joined and grouped in order to detect prolonged spiking. In the first step, the allowable time interval between detected spiking seconds is ≤ 4s making block of groups according to the rule. In the second step these blocks are rearranged to bigger blocks according to the rule, that the allowable time gap between blocks is ≤ 12 s.

Amplitude levels in spiking area grew on average 1.7 times compared to non -spiking area of studied 11 patients making possible to detect spiking seconds and allowing prolonged spiking episodes to be sorted out from these seconds. On average 17.3% of the visually inspected and visually scored IFF episode duration seconds were detected as prolonged spiking seconds according to the conditions set for detection from studied 11 patients.

Automatic detection of spiking events in EMFi sheet during sleep 

Jarmo Alametsä, Esa Rauhala , Eero Huupponen, Antti Saastamoinen, Alpo Varri, Atte Joutsen, Joel Hasan, Sari-Leena Himanen 

Medical Engineering & Physics 28 (2006) 267–275

Abstract: In this paper we present a new method for detection of spiking events caused by the increased respiratory resistance (IRR) from ballistocardiographic (BCG) data recorded with EMFi sheet. Spiking is a phenomenon where BCG wave complexes increase in amplitude during IRR. In this study data from six patients with a total of 1503 visually scored spiking events were studied. The algorithm monitors amplitude levels of BCG complexes and detects large relative increases. In this work 10 different variations of the algorithm were compared in order to find the best variation, which can cope with different recordings. The best variation of the algorithm was able to detect spiking events with 80% true positive and 19% false positive rates. The detection is not dependent on absolute waveform amplitudes and therefore does not require any recording-specific tuning prior to application. It is important to recognize spiking events in order to evaluate the severity of respiratory disturbance during sleep. 

© 2005 IPEM. Published by Elsevier Ltd.

Performance of Non-invasive Devices in Evaluation of Periodic Limb Movements and Sleep-disordered Breathing

Esa Rauhala

Doctoral Thesis, Faculty of Medicine of the University of Tampere, 2009.

Abstract: Polysomnography is considered as the gold standard in diagnosing sleep disturbances. These studies are quite expensive as they are performed in sleep laboratories with continuous attendance by a technician or nurse. Recordings with large amounts of cables and measurement devices can be inconvenient for the patients. Therefore there is a constant need to develop ambulatory, unmolested, inexpensive but reliable methods for clinical sleep investigations.

The aim of this thesis was to study the suitability of mattress type movement sensors for the detection of periodic limb movements and in the characterization of sleep-disordered breathing. Also the performance of a new method, compressed tracheal sound analysis, in the evaluation of sleep-disordered breathing is presented in the thesis.

Patients with restless leg syndrome have very often periodic limb movements in their sleep recordings. This finding is considered as a supportive criterion in restless legs diagnostics. The gold standard in recording of periodic limb movements is anterior tibialis electromyography. The studies in this thesis showed that the static-charge-sensitive bed (SCSB) and Emfit sensors detect periodic limb movements reliably and the periodic movement indexes were quite comparable with the gold standard.

A special signal feature, a spiking phenomenon is seen with both the SCSB and Emfit sensors. Spiking can also reliably be detected with an automatic method that does not need any recording-specific tuning before the analysis. In sleep-disordered breathing prolonged spiking was found to be associated with an increase in transcutaneously measured carbon dioxide (TcCO2). During apnea and hypopnea episodes no significant change in TcCO2 level was observed. The non-round inspiratory flow shapes, which are related to flow limitation, were most constant phenomenon during prolonged spiking episodes.

Snoring is very often associated with sleep-disordered breathing and an important reason for referrals to sleep studies. Analyses of snoring and tracheal sound can be used in the evaluation of sleep related breathing disorders. In the compressed tracheal sound analysis the signal curve can visually be divided into three distinct patterns. The characteristics of the patterns differed significantly from each other. Based on the diverse appearances of the patterns, breathing with apneas/hypopneas, flow limitation and normal breathing could be distinguished.

The studied non-invasive methods, the SCSB and Emfit seem to be suitable for detecting periodic limb movements. Emfit and compressed tracheal sound analysis can help in the evaluation of sleep-disordered breathing. They all can be used as parts of larger recording systems or even as stand-alone devices.  The recordings are inexpensive, easy to perform and cause minimal if any disturbance to a patient. Thus they are very suitable for ambulatory sleep recording systems. Additionally, they all have special features that can detect and characterize the still poorly understood prolonged flow limitation.

Periodic limb movement screening as an additional feature of Emfit sensor in sleep-disordered breathing studies

Esa Rauhala, Jussi Virkkala, Sari-Leena Himanen

Journal of Neuroscience Methods 178 (2009) 157–161

Abstract: The standardmethod for recording periodic limb movements is anterior tibialis electromyography (EMG) but other methods are also used. A new movement sensor Emfit (ElectroMechanical Film) provides information about sleep-disordered breathing but also shows movements in bed. The aim of the study was to investigate the usability of a small Emfit sensor in revealing periodic movements. Methods: Twenty seven consecutive patients were studied. Periodic movements in EMG and Emfit were scored blindly and periodic leg movement index (PLMI) for EMG and periodic movement index (PMI) for Emfit were counted. Spearman’s correlation coefficient was used to assess the relationship between Emfit data and EMG results. Sensitivities and specificities were computed for PLMI and PMI levels of 5 and 15 movements/h. Additionally, receiver operating characteristic (ROC) curves were derived and the area under the curve (AUC) was calculated. Results: The Spearman’s correlation coefficient between the PMI of Emfit and the PLMI of EMG was 0.87. The sensitivity of the Emfit sensor to detect periodic limb movements was 0.91 at the level of 5movements/h and 0.73 when the cut-off level was 15movements/h. The specificities were 0.75 and 1.00, respectively. AUC in ROC analysis was 0.96 and 0.98 in the levels of 5 and 15movements/h. Conclusions: The results suggest that the Emfit sensor might be suitable for screening of periodic limb movements even if the sensor is placed under the thoracic area of the patient in sleep-disordered breathing studies.

© 2008 Elsevier B.V.

Screening sleep-related breathing disturbances in stroke patients using the Emfit ferroelectret film sensor and the oximeter

T.S. Niiniviita*1, M. Takala1,2, E. Rauhala2 and A. Holm1,2

1 University of Turku, University of Turku Graduate School, Turku, Finland

2 Satakunta Central Hospital, Department of Clinical Neurophysiology, Pori, Finland 

© EMBEC NBC 2017 Abstract Book 


Sleep-related breathing disturbances (SDB) are present in 50 – 70 % of stroke patients and can have a negative effect on the recovery. Therefore, screening for SDB in all stroke patients is recommended. Continuous positive airway pressure (CPAP) is the recommended treatment [1]. Screening of all stroke patients for SDB by standard is typically not possible due to the lack of staff resources implying a need for a less laborious screening method.

The aim of the study was to evaluate if Emfit sleep mattress (Emfit Ltd, Vaajakoski, Finland) and oximeter (Nox Medical, Reyjavik, Iceland) could be used as a screening method to identify stroke patients with suspected moderate or severe sleep apnea.


We studied a group of 41 patients, who were hospitalized for stroke and had not been diagnosed with sleep apnea before. These patients underwent simultaneous respiratory polygraphy and Emfit mattress measurement during the night. The standard polygraphy included respiratory inductance plethysmography, oximeter, nasal flow measurement and EKG. Emfit mattress measurement included a ferroelectret film sensor which was positioned under the bed mattress and the oximeter signal from polygraphy measurement.

Polygraphy was scored automatically using Noxturnal (Nox Medical, Reyjavik, Iceland) Respiratory Cannula Flow analy- sis and visually according AASM criteria (=golden standard). Emfit data was scored automatically using Noxturnal modified flow analysis.

The patients were classified into four categories according to the automatic scorings of Apnea-Hypopnea Index. The cate- gorizations obtained from both methods were compared using receiver operating characteristics curves. We also evaluated the concurrence and consistency of events (desaturation, hypopnea or apnea) in both methods.


Comparison of automatic analyses revealed that 89 % of Emfit events were overlapping with polygraphy events. However, only 46 % of them were classified similarly. When compared to visual scoring polygraphy had sensitivity of 92 % and specificity of 79 %, Emfit mattress had sensitivity of 100 % and specificity of 82 %.


The Emfit mattress and oximeter seems to be promising method to screen out stroke patients with moderate and severe sleep apnea. However, the automatic analysis must be improved to be more accurate. Improving the accuracy of the automatic analysis is the aim of the following study.


The authors declare that they have no conflict of interest.



Hermann DM, Bassetti CL (2009) Sleep-related breathing and sleep- wake disturbances in ischemic stroke. Neurology 73:1313-132

Excerpts of Doctoral Thesis, Mirja Tenhunen; “Detection and Assessment of Sleep-Disordered Breathing with Special Interest of Prolonged Partial Obstruction”, Faculty of Medicine of the University of Tampere, 2015.

© Tampereen teknillinen yliopisto - Tampere University of Technology 2015



© Tampereen teknillinen yliopisto - Tampere University of Technology 2015


© Tampereen teknillinen yliopisto - Tampere University of Technology 2015



© Tampereen teknillinen yliopisto - Tampere University of Technology 2015



© Tampereen teknillinen yliopisto - Tampere University of Technology 2015



© Tampereen teknillinen yliopisto - Tampere University of Technology 2015


Excerpt of Prolonged partial upper airway obstruction during sleep  an underdiagnosed phenotype of sleep-disordered breathing Ulla Anttalainen, Mirja Tenhunen, Ville Rimpila, Olli Polo, Esa Rauhala, Sari-Leena Himanen and Tarja Saaresranta, Published: 6 September 2016, EUROPEAN CLINICAL RESPIRATORY JOURNAL


Example of a 5-min polysomnography period. At the beginning of the sheet, respiratory movements are stable; flow channel shows slight flow limitation and mouth breathing. Negative esophageal pressure is increased up to 30 cm H2O. Emfit high-frequency channel shows multiple spikes. At the middle of sheet (marked with a black arrow) is a short arousal with opening of upper airway, normalizing esophageal pressure values and cease of spiking. Gradually breathing effort starts to increase again. Channels from top: thoracic and abdominal belts, flow by nasal pressure transducer, esophageal pressure, Emfit high-frequency channel, Emfit low-frequency channel, arterial oxyhemoglobin saturation, snoring, and pulse.


For sleep research needs Emfit QS has as optional feature the band-pass filtered sensor signal visualisation. Low band is 0,1 - 3 Hz and high band is 6 - 16 Hz. User interface is designed for easy use, for example amplitude and time span on screen can be widely adjusted.


Emfit QS (physical product with web and phone application) is a general wellness product for healthy adults at home and in institutional care environments. Information obtained is intended for use (I) in evaluating a healthy individual waking hours activities impact on his or her recovery and sleep quality, (II) in monitoring a healthy individual who, when not in bed, is in the risk of (a) falling, (b) interfering others, or (c) wandering. In the above mentioned purposes it is not a medical device and is not intended for the diagnosis or monitoring of any disease or to investigate a physiological process.