Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas.

The combination of DNA methylation analysis with histopathological and genetic features allows for a more accurate risk stratification and classification of meningiomas. Nevertheless, the implications of this classification for patients with grade 2 meningiomas, a particularly heterogeneous tumor entity, are only partially understood. We correlate the outcomes of histopathologically confirmed grade 2 meningioma with an integrated molecular-morphologic risk stratification and determine its clinical implications. Grade 2 meningioma patients treated at our institution were re-classified using an integrated risk stratification involving DNA methylation array-based data, copy number assessment and TERT promoter mutation analyses. Grade 2 meningioma cases according to the WHO 2021 criteria treated between 2007 and 2021 (n = 100) were retrospectively analyzed. The median clinical and radiographic follow-up periods were 59.8 and 54.4 months. A total of 38 recurrences and 17 deaths were observed. The local control rates of the entire cohort after 2-, 4-, and 6-years were 84.3%, 68.5%, and 50.8%, with a median local control time of 77.2 months. The distribution of the integrated risk groups were as follows: 31 low, 54 intermediate, and 15 high risk cases. In the multivariable Cox regression analysis, integrated risk groups were significantly associated with the risk of local recurrence (hazard ratio (HR) intermediate: 9.91, HR high-risk: 7.29, p < 0.01). Gross total resections decreased the risk of local tumor progression (HR gross total resection: 0.19, p < 0.01). The comparison of 1p status and integrated risk groups (low vs. intermediate/high) revealed nearly identical local control rates within their respective subgroups. In summary, only around 50% of WHO 2021 grade 2 meningiomas have an intermediate risk profile. Integrated molecular risk stratification is crucial to guide the management of patients with grade 2 tumors and should be routinely applied to avoid over- and undertreatment, especially concerning the use of adjuvant radiotherapy.

Eliminating the Trade-off Between Resolution and Sampling Rate in Magnetic Induction Based Cardiorespiratory Sensors.

This paper proposes a novel algorithm that allows a significant improvement of the resolution of frequency modulated magnetic induction sensors while providing high sampling rates. We have implemented this approach in a frequency modulated magnetic induction sensor and our first measurements demonstrate the improvement of the sensor's signal quality.

A Novel Type of IDH-wildtype Glioma Characterized by Gliomatosis Cerebri-like Growth Pattern, TERT Promoter Mutation, and Distinct Epigenetic Profile.

Diffuse gliomas in adults encompass a heterogenous group of central nervous system neoplasms. In recent years, extensive (epi-)genomic profiling has identified several glioma subgroups characterized by distinct molecular characteristics, most importantly IDH1/2 and histone H3 mutations. A group of 16 diffuse gliomas classified as "adult-type diffuse high-grade glioma, IDH-wildtype, subtype F (HGG-F)" was identified by the DKFZ v12.5 Brain Tumor Classifier . Histopathologic characterization, exome sequencing, and review of clinical data was performed in all cases. Based on unsupervised t -distributed stochastic neighbor embedding and clustering analysis of genome-wide DNA methylation data, HGG-F shows distinct epigenetic profiles separate from established central nervous system tumors. Exome sequencing demonstrated frequent TERT promoter (12/15 cases), PIK3R1 (11/16), and TP53 mutations (5/16). Radiologic characteristics were reminiscent of gliomatosis cerebri in 9/14 cases (64%). Histopathologically, most cases were classified as diffuse gliomas (7/16, 44%) or were suspicious for the infiltration zone of a diffuse glioma (5/16, 31%). None of the cases demonstrated microvascular proliferation or necrosis. Outcome of 14 patients with follow-up data was better compared to IDH-wildtype glioblastomas with a median progression-free survival of 58 months and overall survival of 74 months (both P <0.0001). Our series represents a novel type of adult-type diffuse glioma with distinct molecular and clinical features. Importantly, we provide evidence that TERT promoter mutations in diffuse gliomas without further morphologic or molecular signs of high-grade glioma should be interpreted in the context of the clinicoradiologic presentation as well as epigenetic profile and may not be suitable as a standalone marker for glioblastoma, IDH-wildtype.

Mucosal melanomas of different anatomic sites share a common global DNA methylation profile with cutaneous melanoma but show location-dependent patterns of genetic and epigenetic alterations.

Cutaneous, ocular, and mucosal melanomas are histologically indistinguishable tumors that are driven by a different spectrum of genetic alterations. With current methods, identification of the site of origin of a melanoma metastasis is challenging. DNA methylation profiling has shown promise for the identification of the site of tumor origin in various settings. Here we explore the DNA methylation landscape of melanomas from different sites and analyze if different melanoma origins can be distinguished by their epigenetic profile. We performed DNA methylation analysis, next generation DNA panel sequencing, and copy number analysis of 82 non-cutaneous and 25 cutaneous melanoma samples. We further analyzed eight normal melanocyte cell culture preparations. DNA methylation analysis separated uveal melanomas from melanomas of other primary sites. Mucosal, conjunctival, and cutaneous melanomas shared a common global DNA methylation profile. Still, we observed location-dependent DNA methylation differences in cancer-related genes, such as low frequencies of RARB (7/63) and CDKN2A promoter methylation (6/63) in mucosal melanomas, or a high frequency of APC promoter methylation in conjunctival melanomas (6/9). Furthermore, all investigated melanomas of the paranasal sinus showed loss of PTEN expression (9/9), mainly caused by promoter methylation. This was less frequently seen in melanomas of other sites (24/98). Copy number analysis revealed recurrent amplifications in mucosal melanomas, including chromosomes 4q, 5p, 11q and 12q. Most melanomas of the oral cavity showed gains of chromosome 5p with TERT amplification (8/10), while 11q amplifications were enriched in melanomas of the nasal cavity (7/16). In summary, mucosal, conjunctival, and cutaneous melanomas show a surprisingly similar global DNA methylation profile and identification of the site of origin by DNA methylation testing is likely not feasible. Still, our study demonstrates tumor location-dependent differences of promoter methylation frequencies in specific cancer-related genes together with tumor site-specific enrichment for specific chromosomal changes and genetic mutations. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Molecular characterisation of sporadic endolymphatic sac tumours and comparison to von Hippel-Lindau disease-related tumours.

AIMS: Although inactivation of the von Hippel-Lindau gene (VHL) on chromosome 3p25 is considered to be the major cause of hereditary endolymphatic sac tumours (ELSTs), the genetic background of sporadic ELST is largely unknown. The aim of this study was to determine the prevalence of VHL mutations in sporadic ELSTs and compare their characteristics to VHL-disease-related tumours. METHODS: Genetic and epigenetic alterations were compared between 11 sporadic and 11 VHL-disease-related ELSTs by targeted sequencing and DNA methylation analysis. RESULTS: VHL mutations and small deletions detected by targeted deep sequencing were identified in 9/11 sporadic ELSTs (82%). No other cancer-related genetic pathway was altered except for TERT promoter mutations in two sporadic ELST and one VHL-disease-related ELST (15%). Loss of heterozygosity of chromosome 3 was found in 6/10 (60%) VHL-disease-related and 10/11 (91%) sporadic ELSTs resulting in biallelic VHL inactivation in 8/10 (73%) sporadic ELSTs. DNA methylation profiling did not reveal differences between sporadic and VHL-disease-related ELSTs but reliably distinguished ELST from morphological mimics of the cerebellopontine angle. VHL patients were significantly younger at disease onset compared to sporadic ELSTs (29 vs. 52 years, p < 0.0001, Fisher's exact test). VHL-disease status was not associated with an increased risk of recurrence, but the presence of clear cells was found to be associated with shorter progression-free survival (p = 0.0002, log-rank test). CONCLUSION: Biallelic inactivation of VHL is the main mechanism underlying ELSTs, but unknown mechanisms beyond VHL may rarely be involved in the pathogenesis of sporadic ELSTs.

Identification of dental pain sensation based on cardiorespiratory signals.

The aim of this study is to investigate the feasibility of the detection of brief periods of pain sensation based on cardiorespiratory signals during dental pain triggers. Twenty patients underwent dental treatment and reported their pain events by pressing a push button while ECG, PPG, and thoracic effort signals were simultaneously recorded. Potential pain-indicating features were calculated from the physiological data (sample length of 6 s) and were used for supervised learning of a Random forest pain detector. The best feature combination was determined by Feature forward selection. The best feature combination comprises nine feature groups consisting of four respiratory and five cardiac related groups. The final algorithm achieved a sensitivity of 87% and a specificity of 63% with an AUC of 0.828. Using supervised learning it is possible to train an algorithm to differentiate between short time intervals of pain and no pain solely based on cardiorespiratory signals. An on-site and real-time detection and rating of pain sensations would allow a precise, individuum- and treatment-tailored administration of local anesthesia. Severe phases of pain could be paused or avoided, this would allow more comfortable treatment and yield better patient compliance.

Classification of chronic venous diseases based on skin temperature patterns.

Objective. Infrared thermography has the potential to complement the classification of chronic venous diseases (CVD), but lacks sophisticated insights on the association between recorded skin temperatures and the severity of CVD. This research aims to identify temperature patterns in the lower legs of patients that are distinct in specific forms of CVD, including florid ulcers.Approach. Infrared images were acquired in a clinical trial with 36 patients and segmented using a region selection algorithm. The regions were analyzed with respect to seven predefined features. The most prominent thermal features were translated into rules to classify CVD.Main results. Patients with mild forms of CVD show local increases in skin temperature by more than 1.5 °C. These regions were 2.0 °C warmer when CVD is more severe. Temperature variations of on average 0.4 °C occurred within venous leg ulcers. Furthermore, these wounds were 1.1 °C-6.3 °C colder than periwound skin.Significance. Temperature patterns characterized by differences in temperature that occur within a few centimeters or millimeters are distinct to specific stages of CVD. These patterns are present in the locations of varicose veins and tissue damages.Significance. The findings increase the body of knowledge on the potential for the early detection of CVD using infrared thermography. Applying the presented algorithms and rules, infrared thermography may become a complementary tool for the objective classification of CVD.

Distortion of the Intracranial Pressure Waveform by Extraventricular Drainage System.

OBJECTIVE: To investigate whether intracranial pressure (ICP) waveform measurements obtained from extraventricular drainage (EVD) systems are suitable for the calculation of intracranial elastance (ICE) or cerebrovascular pressure autoregulation (PAR) indices. METHODS: The transfer characteristic of an EVD system is investigated by its step and frequency responses with focus on the low frequency (LF) range from 0.02 to 0.065 Hz (important in PAR) and the location of the system's first resonance frequency (important for ICE). The effects of opening the distal end of the EVD for drainage of cerebrospinal fluid and the presence of trapped air bubbles are also investigated. RESULTS: The EVD system exhibits a first resonant frequency below 4 Hz, resulting in significant distortion of the measured ICP waveform. The frequency response in the LF range only remains flat when the EVD is closed. Opening the drain results in drops in magnitude and phase along the entire frequency range above DC. Air bubbles close to the EVD catheter tip affect the LF range while an air bubble close to the pressure transducer further decreases the first resonant frequency. Tests with actual ICP waveforms confirmed EVD-induced waveform distortions that can lead to erroneous ICE estimation. CONCLUSION: EVD-based ICP measurements distort the waveform morphology. PAR indices based on LF information are only valid if the EVD is closed. EVD-based ICE estimation is to be avoided. SIGNIFICANCE: ICP waveform analyses to derive information about ICE and PAR should be critically questioned if only EVD derived ICP signals are at hand.

Molecular characterization of CNS paragangliomas identifies cauda equina paragangliomas as a distinct tumor entity.

Paragangliomas/pheochromocytomas are rare neuroendocrine tumors that arise from the adrenal gland or ganglia at various sites throughout the body. They display a remarkable diversity of driver alterations and are associated with germline mutations in up to 40% of the cases. Comprehensive molecular profiling of abdomino-thoracic paragangliomas revealed four molecularly defined and clinically relevant subtypes. Paragangliomas of the cauda equina region are considered to belong to one of the defined molecular subtypes, but a systematic molecular analysis has not yet been performed. In this study, we analyzed genome-wide DNA methylation profiles of 57 cauda equina paragangliomas and show that these tumors are epigenetically distinct from non-spinal paragangliomas and other tumors. In contrast to paragangliomas of other sites, chromosomal imbalances are widely lacking in cauda equina paragangliomas. Furthermore, RNA and DNA exome sequencing revealed that frequent genetic alterations found in non-spinal paragangliomas-including the prognostically relevant SDH mutations-are absent in cauda equina paragangliomas. Histologically, cauda equina paragangliomas show frequently gangliocytic differentiation and strong immunoreactivity to pan-cytokeratin and cytokeratin 18, which is not common in paragangliomas of other sites. None of our cases had a familial paraganglioma syndrome. Tumors rarely recurred (9%) or presented with multiple lesions within the spinal compartment (7%), but did not metastasize outside the CNS. In summary, we show that cauda equina paragangliomas represent a distinct, sporadic tumor entity defined by a unique clinical and morpho-molecular profile.

Machine learning analysis of DNA methylation profiles distinguishes primary lung squamous cell carcinomas from head and neck metastases.

Head and neck squamous cell carcinoma (HNSC) patients are at risk of suffering from both pulmonary metastases or a second squamous cell carcinoma of the lung (LUSC). Differentiating pulmonary metastases from primary lung cancers is of high clinical importance, but not possible in most cases with current diagnostics. To address this, we performed DNA methylation profiling of primary tumors and trained three different machine learning methods to distinguish metastatic HNSC from primary LUSC. We developed an artificial neural network that correctly classified 96.4% of the cases in a validation cohort of 279 patients with HNSC and LUSC as well as normal lung controls, outperforming support vector machines (95.7%) and random forests (87.8%). Prediction accuracies of more than 99% were achieved for 92.1% (neural network), 90% (support vector machine), and 43% (random forest) of these cases by applying thresholds to the resulting probability scores and excluding samples with low confidence. As independent clinical validation of the approach, we analyzed a series of 51 patients with a history of HNSC and a second lung tumor, demonstrating the correct classifications based on clinicopathological properties. In summary, our approach may facilitate the reliable diagnostic differentiation of pulmonary metastases of HNSC from primary LUSC to guide therapeutic decisions.

Intracranial Pressure and Intracranial Elastance Monitoring in Neurocritical Care.

Patients with acute brain injuries tend to be physiologically unstable and at risk of rapid and potentially life-threatening decompensation due to shifts in intracranial compartment volumes and consequent intracranial hypertension. Invasive intracranial pressure (ICP) monitoring therefore remains a cornerstone of modern neurocritical care, despite the attendant risks of infection and damage to brain tissue arising from the surgical placement of a catheter or pressure transducer into the cerebrospinal fluid or brain tissue compartments. In addition to ICP monitoring, tracking of the intracranial capacity to buffer shifts in compartment volumes would help in the assessment of patient state, inform clinical decision making, and guide therapeutic interventions. We review the anatomy, physiology, and current technology relevant to clinical management of patients with acute brain injury and outline unmet clinical needs to advance patient monitoring in neurocritical care.

A Multi-Modal Sensor for a Bed-Integrated Unobtrusive Vital Signs Sensing Array.

In this paper, we present a novel unobtrusive multi-modal sensor for monitoring of physiological parameters featuring capacitive electrocardiogram (cECG), reflective photoplethysmogram (rPPG), and magnetic induction monitoring (MI) in a single sensor. The sensor system comprises sensor nodes designed and optimized for integration into a grid-like array of multiple sensors in a bed and a central controller box for data collection and processing. Hence, it is highly versatile in application and suitable for unobtrusive monitoring of vital signs, both in a professional setting and a home-care environment. The presented hardware design takes both inter-modal interference between cECG and MI into account as well as intra-modal interference due to cross talk between two MI sensors in close vicinity. In a lab study, we evaluated a prototype of our new multi-modal sensor with two sensor nodes on four healthy subjects. The subjects were lying on the sensors and exercising with a hand grip in order to increase heart rate and thus evaluate our sensor both during changing physiological parameters as well as a wider range of those. Heart beat intervals and heart rate variability were derived from both cECG and rPPG. Breathing intervals were derived from the MI sensor. For heart beat intervals, we achieved an RMSE of 2.3 ms and a correlation of 0.99 using cECG. Similarly, using rPPG, an RMSE of 18.9 ms with a correlation of 0.99 was achieved. With regard to breathing intervals derived from MI, we achieved an RMSE of 1.12 s and a correlation of 0.90.

Capacitive ECG Monitoring in Cardiac Patients During Simulated Driving.

OBJECTIVE: This study aims to compare the informative value of a capacitively coupled electrocardiogram (cECG) to a conventional galvanic reference ECG (rECG) in patients after a major cardiac event under simulated driving conditions. Addressed research questions are the comparison and coherence of cECG and rECG by means of the signal quality, the artifact rate, the rate of assessable data for differential diagnosis, the visibility of characteristic ECG structures in cECG, the precision of ECG time intervals, and heart rate (in particular, despite possible waveform deformations due to the cardiac preconditions). METHODS: In a clinical trial, cECG and rECG data were recorded from ten patients after a major cardiac event. The cECG and rECG data were blindly evaluated by two cardiologists with regard to signal quality, artifacts, assessable data for differential diagnosis, visibility of ECG structures, and ECG time intervals. The results were statistically compared. RESULTS: The cECG presented with more artifacts, an inferior signal quality, and less assessable data. However, when the data were assessable, determination of the ECG interval lengths was coherent to the one obtained from the rECG. CONCLUSION: When the signal quality is sufficient, the cECG yields the same informative value as the rECG. SIGNIFICANCE: For certain scenarios, cECG might replace rECG systems. Hence, it is an important research question whether a similar amount of information can be obtained using a cECG system.

Noncontact Monitoring of Respiratory Rate in Newborn Infants Using Thermal Imaging.

Monitoring of respiratory rate (RR) is very important for patient assessment. In fact, it is considered one of the relevant vital parameters in critical care medicine. Nowadays, standard monitoring relies on obtrusive and invasive techniques, which require adhesive electrodes or sensors to be attached to the patient's body. Unfortunately, these procedures cause stress, pain, and frequently damage the vulnerable skin of preterm infants. This paper presents a "black-box" algorithm for remote monitoring of RR in thermal videos. "Black-box" in this context means that the algorithm does not rely on tracking of specific anatomic landmarks. Instead, it automatically distinguishes regions of interest in the video containing the respiratory signal from those containing only noise. To examine its performance and robustness during physiological (phase A) and pathological scenarios (phase B), a study on 12 healthy volunteers was carried out. After a successful validation on adults, a clinical study on eight newborn infants was conducted. A good agreement between estimated RR and ground truth was achieved. In the study involving adult volunteers, a mean root-mean-square error (RMSE) of ( 0.31 ±0.09) breaths/min and ( 3.27 ±0.72) breaths/min was obtained for phase A and phase B, respectively. In the study involving infants, the mean RMSE hovered around ( 4.15 ±1.44) breaths/min. In brief, this paper demonstrates that infrared thermography might become a clinically relevant alternative for the currently available RR monitoring modalities in neonatal care.

Non-Contact Remote Measurement of Heart Rate Variability using Near-Infrared Photoplethysmography Imaging.

Heart rate variability (HRV) is an important clinical parameter associated with the autonomous nervous system (ANS), age, as well as many diseases such as myocardial infarction, diabetes or renal failure. Gold standard for measurement of HRV is a high-resolution electrocardiogram (ECG). With the current trend towards non-contact and unobtrusive monitoring of vital signs, HRV has also become an interesting and important parameter for non-contact monitoring. In this paper, we present an approach towards non-contact and unobtrusive monitoring of heart rate variability using the camera-based technology of photoplethysmography imaging (PPGI). We investigated the suitability of invisible near-infrared illumination for PPGI, which would enable measurement of HRV in darkness. We compared results obtained using infrared illumination with those obtained using visible light as PPGI illumination and calculated both time-domain as well as frequency-domain HRV parameters. The results achieved with infrared illumination were on par with those using conventional illumination in the visible spectrum. We concluded that infrared illumination enables unobtrusive and non-contact remote HRV measurement in both darkness as well as regular daylight conditions using PPGI.

Fusing non-contact vital sign sensing modalities - first results.

A wearable multi-sensor system allowing synchronized unobtrusive measurements of 4 vital signs at a dedicated location of interest is presented. The 4×U sensor is capable of synchronously measuring magnetic impedance, reflective photoplethysmography, capacitive electrocardiogram and seismocardiography (ballistocardiography). The hardware of all modalities is described and some preliminary results are reported.

Unobtrusive Vital Sign Monitoring in Automotive Environments-A Review.

This review provides an overview of unobtrusive monitoring techniques that could be used to monitor some of the human vital signs (i.e., heart activity, breathing activity, temperature and potentially oxygen saturation) in a car seat. It will be shown that many techniques actually measure mechanical displacement, either on the body surface and/or inside the body. However, there are also techniques like capacitive electrocardiogram or bioimpedance that reflect electrical activity or passive electrical properties or thermal properties (infrared thermography). In addition, photopleythysmographic methods depend on optical properties (like scattering and absorption) of biological tissues and-mainly-blood. As all unobtrusive sensing modalities are always fragile and at risk of being contaminated by disturbances (like motion, rapidly changing environmental conditions, triboelectricity), the scope of the paper includes a survey on redundant sensor arrangements. Finally, this review also provides an overview of automotive demonstrators for vital sign monitoring.

Detection of acute periodontal pain from physiological signals.

OBJECTIVE: To investigate the feasibility of the detection of brief orofacial pain sensations from easily recordable physiological signals by means of machine learning techniques. APPROACH: A total of 47 subjects underwent periodontal probing and indicated each instance of pain perception by means of a push button. Simultaneously, physiological signals were recorded and, subsequently, autonomic indices were computed. By using the autonomic indices as input features of a classifier, a pain indicator based on fusion of the various autonomic mechanisms was achieved. Seven patients were randomly chosen for the test set. The rest of the data were utilized for the validation of several classifiers and feature combinations by applying leave-one-out-cross-validation. MAIN RESULTS: During the validation process the random forest classifier, using frequency spectral bins of the ECG, wavelet level energies of the ECG and PPG, PPG amplitude, and SPI as features, turned out to be the best pain detection algorithm. The final test of this algorithm on the independent test dataset yielded a sensitivity and specificity of 71% and 70%, respectively. SIGNIFICANCE: Based on these results, fusion of autonomic indices by applying machine learning techniques is a promising option for the detection of very brief instances of pain perception, that are not covered by the established indicators.

Practical implementation of DNA methylation and copy-number-based CNS tumor diagnostics: the Heidelberg experience.

Recently, we described a machine learning approach for classification of central nervous system tumors based on the analysis of genome-wide DNA methylation patterns [6]. Here, we report on DNA methylation-based central nervous system (CNS) tumor diagnostics conducted in our institution between the years 2015 and 2018. In this period, more than 1000 tumors from the neurosurgical departments in Heidelberg and Mannheim and more than 1000 tumors referred from external institutions were subjected to DNA methylation analysis for diagnostic purposes. We describe our current approach to the integrated diagnosis of CNS tumors with a focus on constellations with conflicts between morphological and molecular genetic findings. We further describe the benefit of integrating DNA copy-number alterations into diagnostic considerations and provide a catalog of copy-number changes for individual DNA methylation classes. We also point to several pitfalls accompanying the diagnostic implementation of DNA methylation profiling and give practical suggestions for recurring diagnostic scenarios.

Monitoring of Cardiorespiratory Signals Using Thermal Imaging: A Pilot Study on Healthy Human Subjects.

Heart rate (HR) and respiratory rate (RR) are important parameters for patient assessment. However, current measurement techniques require attachment of sensors to the patient’s body, often leading to discomfort, stress and even pain. A new algorithm is presented for monitoring both HR and RR using thermal imaging. The cyclical ejection of blood flow from the heart to the head (through carotid arteries and thoracic aorta) leads to periodic movements of the head; these vertical movements are used to assess HR. Respiratory rate is estimated by using temperature fluctuations under the nose during the respiratory cycle. To test the viability and feasibility of this approach, a pilot study was conducted with 20 healthy subjects (aged 18⁻36 and 1 aged 50 years). The study consisted of two phases: phase A (frontal view acquisitions) and phase B (side view acquisitions). To validate the results, photoplethysmography and thoracic effort (piezoplethysmography) were simultaneously recorded. High agreement between infrared thermography and ground truth/gold standard was achieved. For HR, the root-mean-square errors (RMSE) for phases A and B were 3.53 ± 1.53 and 3.43 ± 1.61 beats per minute, respectively. For RR, the RMSE between thermal imaging and piezoplethysmography stayed around 0.71 ± 0.30 breaths per minute (phase A). This study demonstrates that infrared thermography may be a promising, clinically relevant alternative for the assessment of HR and RR.