Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension

Elevated blood pressure (BP) is a major cause of death, yet hypertension commonly goes undetected. Owing to its nature, it is typically asymptomatic until later in its progression when the vessel or organ structure has already been compromised. Therefore, noninvasive and continuous BP measurement methods are needed to ensure appropriate diagnosis and early management before hypertension leads to irreversible complications. Photoplethysmography (PPG) is a noninvasive technology with waveform morphologies similar to that of arterial BP waveforms, therefore attracting interest regarding its usability in BP estimation. In recent years, wearable devices incorporating PPG sensors have been proposed to improve the early diagnosis and management of hypertension. Additionally, the need for improved accuracy and convenience has led to the development of devices that incorporate multiple different biosignals with PPG. Through the addition of modalities such as an electrocardiogram, a final measure of the pulse wave velocity is derived, which has been proved to be inversely correlated to BP and to yield accurate estimations. This paper reviews and summarizes recent studies within the period 2010-2019 that combined PPG with other biosignals and offers perspectives on the strengths and weaknesses of current developments to guide future advancements in BP measurement. Our literature review reveals promising measurement accuracies and we comment on the effective combinations of modalities and success of this technology

The 2023 wearable photoplethysmography roadmap

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure.

The diagnosis of hypertension and the adjustment of antihypertensive drugs are evolving from isolated measurements performed at the physician offices to the full phenotyping of patients in real-life conditions. Indeed, the strongest predictor of cardiovascular risk comes from night measurements. The aim of this study was to demonstrate that a wearable device (the Aktiia Bracelet) can accurately estimate BP in the most common body positions of daily life and thus become a candidate solution for the BP phenotyping of patients. We recruited 91 patients with BP ranging from low to hypertensive levels and compared BP values from the Aktiia Bracelet against auscultatory reference values for 4 weeks according to an extended ISO 81060-2 protocol. After initializing on day one, the observed means and standard deviations of differences for systolic BP were of 0.46 ± 7.75 mmHg in the sitting position, - 2.44 ± 10.15 mmHg in the lying, - 3.02 ± 6.10 mmHg in the sitting with the device on the lap, and - 0.62 ± 12.51 mmHg in the standing position. Differences for diastolic BP readings were respectively of 0.39 ± 6.86 mmHg, - 1.93 ± 7.65 mmHg, - 4.22 ± 6.56 mmHg and - 4.85 ± 9.11 mmHg. This study demonstrates that a wearable device can accurately estimate BP in the most common body positions compared to auscultation, although precision varies across positions. While wearable persistent BP monitors have the potential to facilitate the identification of individual BP phenotypes at scale, their prognostic value for cardiovascular events and its association with target organ damage will need cross-sectional and longitudinal studies. Deploying this technology at a community level may be also useful to drive public health interventions against the epidemy of hypertension

Validation of the optical Aktiia bracelet in different body positions for the persistent monitoring of blood pressure.

The diagnosis of hypertension and the adjustment of antihypertensive drugs are evolving from isolated measurements performed at the physician offices to the full phenotyping of patients in real-life conditions. Indeed, the strongest predictor of cardiovascular risk comes from night measurements. The aim of this study was to demonstrate that a wearable device (the Aktiia Bracelet) can accurately estimate BP in the most common body positions of daily life and thus become a candidate solution for the BP phenotyping of patients. We recruited 91 patients with BP ranging from low to hypertensive levels and compared BP values from the Aktiia Bracelet against auscultatory reference values for 4 weeks according to an extended ISO 81060-2 protocol. After initializing on day one, the observed means and standard deviations of differences for systolic BP were of 0.46 ± 7.75 mmHg in the sitting position, - 2.44 ± 10.15 mmHg in the lying, - 3.02 ± 6.10 mmHg in the sitting with the device on the lap, and - 0.62 ± 12.51 mmHg in the standing position. Differences for diastolic BP readings were respectively of 0.39 ± 6.86 mmHg, - 1.93 ± 7.65 mmHg, - 4.22 ± 6.56 mmHg and - 4.85 ± 9.11 mmHg. This study demonstrates that a wearable device can accurately estimate BP in the most common body positions compared to auscultation, although precision varies across positions. While wearable persistent BP monitors have the potential to facilitate the identification of individual BP phenotypes at scale, their prognostic value for cardiovascular events and its association with target organ damage will need cross-sectional and longitudinal studies. Deploying this technology at a community level may be also useful to drive public health interventions against the epidemy of hypertension

대규모 인구 모델과 단일 가슴 착용형 장치를 활용한 비침습적 연속 동맥 혈압 모니터링 시스템

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2021. 2. 김희찬.최근 수십 년 동안 비침습적 연속 혈압 모니터링에 대한 필요성이 점차 대두되면서 맥파 전달 시간, 맥파 도달 시간, 또는 광용적맥파의 파형으로부터 추출된 다양한 특징들을 이용한 혈압 추정 연구들이 전세계적으로 활발하게 진행되었다. 하지만 대부분의 연구들은 국제 혈압 표준을 만족시키지 못하는 매우 적은 수의 피험자들 만을 대상으로 주로 혈압 추정 모델을 개발 및 검증하였기 때문에 성능의 정확도가 적절하게 검증되지 못했다는 한계점이 있었고, 또한 혈압 추정 파라미터 추출을 위한 생체 신호들을 측정하기 위해 대부분 두 개 이상의 모듈을 필요로 하면서 실용성 측면에서 한계점이 있었다. 첫 번째 연구는 대규모 생체신호 데이터베이스들을 분석함으로써 임상적으로 허용 가능한 수준의 정확도가 적절히 검증된 혈압 추정 모델을 개발하는 것을 목적으로 진행되었다. 본 연구에서는 1376명의 수술 중 환자들의 약 250만 심박 주기에 대해 측정된 두 가지 비침습적 생체신호인 심전도와 광용적맥파를 활용한 혈압 추정 방식들을 분석하였다. 맥파 도달 시간, 심박수, 그리고 다양한 광용적맥파 파형 피처들을 포함하는 총 42 종류의 파라미터들을 대상으로 피처 선택 기법들을 적용한 결과, 28개의 피처들이 혈압 추정 파라미터로 결정되었고, 특히 두 가지 광용적맥파 피처들이 기존에 혈압 추정 파라미터로 가장 주요하게 활용되었던 맥파 도달 시간보다 우월한 파라미터들로 분석되었다. 선정된 파라미터들을 활용하여 혈압의 낮은 주파수 성분을 인공신경망으로 모델링하고, 높은 주파수 성분을 순환신경망으로 모델링 한 결과, 수축기 혈압 에러율 0.05 ± 6.92 mmHg와 이완기 혈압 에러율 -0.05 ± 3.99 mmHg 정도의 높은 정확도를 달성하였다. 또 다른 생체신호 데이터베이스에서 추출한 334명의 중환자들을 대상으로 모델을 외부 검증했을 때 유사한 결과를 획득하면서 세 가지 대표적 혈압 측정 장비 기준들을 모두 만족시켰다. 해당 결과를 통해 제안된 혈압 추정 모델이 1000명 이상의 다양한 피험자들을 대상으로 적용 가능함을 확인하였다. 두 번째 연구는 일상 생활 중 장기간 모니터링이 가능한 단일 착용형 혈압 모니터링 시스템을 개발하는 것을 목적으로 진행되었다. 대부분의 기존 혈압 추정 연구들은 혈압 추정 파라미터 추출을 위해 필요한 생체신호들을 측정하기 위해 두 군데 이상의 신체 지점에 두 개 이상의 모듈을 부착하는 등 실용성 측면에서 한계를 나타냈다. 이를 해결하기 위해 본 연구에서는 심전도와 광용적맥파를 동시에 연속적으로 측정하는 단일 가슴 착용형 디바이스를 개발하였고, 개발된 디바이스를 대상으로 총 25명의 건강한 피험자들로부터 데이터를 획득하였다. 손가락에서 측정된 광용적맥파와 가슴에서 측정된 광용적맥파 간 파형의 특성에 유의미한 차이가 있기 때문에 가슴에서 측정된 광용적맥파에서 추출된 피처들을 대응되는 손가락에서 측정된 광용적맥파 피처들로 특성을 변환하는 전달 함수 모델을 개발하였다. 25명으로부터 획득한 데이터에 전달 함수 모델을 적용시킨 후 혈압 추정 모델을 검증한 결과, 수축기 혈압 에러율 0.54 ± 7.47 mmHg와 이완기 혈압 에러율 0.29 ± 4.33 mmHg로 나타나면서 세 가지 혈압 측정 장비 기준들을 모두 만족시켰다. 결론적으로 본 연구에서는 임상적으로 허용 가능한 수준의 정확도로 장기간 일상 생활이 가능한 비침습적 연속 동맥 혈압 모니터링 시스템을 개발하고 다수의 데이터셋을 대상으로 검증함으로써 고혈압 조기 진단 및 예방을 위한 모바일 헬스케어 서비스의 가능성을 확인하였다.As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many studies on blood pressure (BP) estimation using pulse transit time (PTT), pulse arrival time (PAT), and characteristics extracted from the morphology of photoplethysmogram (PPG) waveform as indicators of BP have been conducted. However, most of the studies have used small homogeneous subject pools to generate models of BP, which led to inconsistent results in terms of accuracy. Furthermore, the previously proposed modalities to measure BP indicators are questionable in terms of practicality, and lack the potential for being utilized in daily life. The first goal of this thesis is to develop a BP estimation model with clinically valid accuracy using a large pool of heterogeneous subjects undergoing various surgeries. This study presents analyses of BP estimation methods using 2.4 million cardiac cycles of two commonly used non-invasive biosignals, electrocardiogram (ECG) and PPG, from 1376 surgical patients. Feature selection methods were used to determine the best subset of predictors from a total of 42 including PAT, heart rate, and various PPG morphology features. BP estimation models were constructed using linear regression, random forest, artificial neural network (ANN), and recurrent neural network (RNN), and the performances were evaluated. 28 features out of 42 were determined as suitable for BP estimation, in particular two PPG morphology features outperformed PAT, which has been conventionally seen as the best non-invasive indicator of BP. By modelling the low frequency component of BP using ANN and the high frequency component using RNN with the selected predictors, mean errors of 0.05 ± 6.92 mmHg for systolic blood pressure (SBP), and -0.05 ± 3.99 mmHg for diastolic blood pressure (DBP) were achieved. External validation of the model using another biosignal database consisting of 334 intensive care unit patients led to similar results, satisfying three international standards concerning the accuracy of BP monitors. The results indicate that the proposed method can be applied to large number of subjects and various subject phenotypes. The second goal of this thesis is to develop a wearable BP monitoring system, which facilitates NCBPM in daily life. Most previous studies used two or more modules with bulky electrodes to measure biosignals such as ECG and PPG for extracting BP indicators. In this study, a single wireless chest-worn device measuring ECG and PPG simultaneously was developed. Biosignal data from 25 healthy subjects measured by the developed device were acquired, and the BP estimation model developed above was tested on this data after applying a transfer function mapping the chest PPG morphology features to the corresponding finger PPG morphology features. The model yielded mean errors of 0.54 ± 7.47 mmHg for SBP, and 0.29 ± 4.33 mmHg for DBP, again satisfying the three standards for the accuracy of BP monitors. The results indicate that the proposed system can be a stepping stone to the realization of mobile NCBPM in daily life. In conclusion, the clinical validity of the proposed system was checked in three different datasets, and it is a practical solution to NCBPM due to its non-occlusive form as a single wearable device.Abstract i Contents iv List of Tables vii List of Figures viii Chapter 1 General Introduction 1 1.1 Need for Non-invasive Continuous Blood Pressure Monitoring (NCBPM) 2 1.2 Previous Studies for NCBPM 5 1.3 Issues with Previous Studies 9 1.4 Thesis Objectives 12 Chapter 2 Non-invasive Continuous Arterial Blood Pressure Estimation Model in Large Population 14 2.1 Introduction 15 2.1.1 Electrocardiogram (ECG) and Photoplethysmogram (PPG) Features for Blood Pressure (BP) Estimation 15 2.1.2 Description of Surgical Biosignal Databases 16 2.2 Feature Analysis 19 2.2.1 Data Acquisition and Data Pre-processing 19 2.2.2 Feature Extraction 25 2.2.3 Feature Selection 35 2.3 Construction of the BP Estimation Models 44 2.3.1 Frequency Component Separation 44 2.3.2 Modelling Algorithms 47 2.3.3 Summary of Training and Validation 52 2.4 Results and Discussion 54 2.4.1 Feature Analysis 54 2.4.1.1 Pulse Arrival Time versus Pulse Transit Time 54 2.4.1.2 Feature Selection 57 2.4.2 Optimization of the BP Estimation Models 63 2.4.2.1 Frequency Component Separation 63 2.4.2.2 Modelling Algorithms 66 2.4.2.3 Comparison against Different Modelling Settings 68 2.4.3 Performance of the Best-case BP Estimation Model 69 2.4.4 Limitations 75 2.5 Conclusion 78 Chapter 3 Development of the Single Chest-worn Device for Non-invasive Continuous Arterial Blood Pressure Monitoring 80 3.1 Introduction 81 3.2 Development of the Single Chest-worn Device 84 3.2.1 Hardware Development 84 3.2.2 Software Development 90 3.2.3 Clinical Trial 92 3.3 Development of the Transfer Function 95 3.3.1 Finger PPG versus Chest PPG 95 3.3.2 The Concept of the Transfer Function 97 3.3.3 Data Acquisition for Modelling of the Transfer Function 98 3.4 Results and Discussion 100 3.4.1 Construction of the Transfer Function 100 3.4.2 Test of the BP Estimation Model 101 3.4.3 Comparison with the Previous Study using the Single Chest-worn Device 104 3.4.4 Limitations 106 3.5 Conclusion 108 Chapter 4 Thesis Summary and Future Direction 109 4.1 Summary and Contributions 110 4.2 Future Work 113 Bibliography 115 Abstract in Korean 129 Acknowledgement 132Docto

Wearable technology and the cardiovascular system: the future of patient assessment

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research

커프리스 방식의 착용형 연속 혈압 모니터링 시스템에 관한 연구

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2019. 2. 김희찬.고혈압의 조기 진단과 고혈압 환자의 혈압 관리를 위해서는 일상생활에서의 지속적인 혈압 모니터링이 중요하다. 맥파전달시간 (Pulse transit time, PTT) 기반의 혈압 추정 방식이 이를 가능케 하는 방법으로 가장 각광 받고 있지만, 맥파전달시간을 측정하기 위해서는 여러 측정 장치들이 필요하여 일상 생활에서의 사용에 제약이 있으며, 또한 맥파전달시간 만을 이용한 수축기 혈압(Systolic blood pressure, SBP) 추정 능력은 부족함이 있는 것으로 알려져 있다. 본 학위 논문의 첫 번째 목적은 맥파전달시간 측정 시스템을 착용형으로 개발하여 간편하게 맥파전달시간을 측정할 수 있도록 함으로써 일상 생활 중 맥파전달시간을 이용한 연속적인 혈압 모니터링이 가능케 하는 것이다. 이를 위해 광용적맥파 (Photoplethysmogram, PPG) 와 심진도 (Seismocardiogram, SCG)를 동시에 측정하는 가슴 착용형 단일 장치를 개발하여, 심진도로부터 대동맥 판막의 열리는 시점을, 광용적맥파로부터 맥파의 도착 시점을 특정하여 맥파 전달 시간을 측정하였다. 개발된 시스템은 낮은 전력 소모와 소형의 간편한 디자인을 통해 24시간 동안 연속적으로 사용할 수 있도록 설계되었다. 측정된 생체신호로부터 추출된 맥파전달시간 및 기타 혈압 관련 변수들이 기기의 반복 착용에도 변하지 않음을 급간내상관계수(Intra-class correlation, ICC) 분석을 통해 확인하였고 (ICC >0.8), 또한 본 시스템에서 사용된 심진도가 대동맥 판막의 열리는 시점의 레퍼런스가 될 수 있는지도 심저항신호(Impedancecardiogram, ICG)와의 비교를 통해 검증하였다(r=0.79±0.14). 둘째로, 개발된 시스템을 이용하여 기존의 맥파 전달 시간만을 이용한 혈압 추정 방식을 보완하여 수축기 혈압의 추정 능력이 향상된 알고리즘을 개발하였다. 이를 위해, 심진도의 진폭과 맥파 전달 시간을 같이 사용하는 다변수 모델을 수축기 혈압 추정을 위해 제안하였고, 다양한 방법으로 유도된 혈압 변화 상황에서, 기존의 맥파전달시간 혹은 맥파도달시간 (Pulse arrival time, PAT) 만을 이용한 모델과 그 성능을 비교하였다. 또한, 제안된 모델이 간단한 교정절차를 통해 여러 사람에게 적용될 수 있는 가능성을 살펴보았고 더 나아가 일상 생활에서의 사용 가능성에 대해서도 검증하였다. 그 결과로 제안된 모델은 (1) 기존의 맥파전달시간 혹은 맥파도달시간 만을 이용한 모델보다 수축기 혈압 추정 능력 측면에서 더 우수하였고, (각각의 평균절대오차는 4.57, 6.01, 6,11 mmHg 였다.) (2) 간단한 교정절차만을 통해서 여러 사람에게 적용 되었을 때의 추정 능력이 국제 기준에 부합하였으며, (3) 일상 생활에서도 사용자의 아무런 개입이나 제약 없이 지속적인 혈압 모니터링이 가능함을 확인하였다. 결론적으로 본 연구에서 제안하는 착용형 연속 혈압 측정 시스템은 가슴에 부착하는 단일 기기 형태로 그 사용이 간편할 뿐 아니라 일상생활 중에서 맥파전달시간과 심진도의 진폭을 이용하여 향상된 수준의 연속 혈압 모니터링 성능을 제공하였는바, 이를 이용한 모바일 헬스케어 서비스의 가능성을 확인하였다.Continuous blood pressure (BP) monitoring is needed in daily life to enable early detection of hypertension and improve control of BP for hypertensive patients. Although the pulse transit time (PTT)-based BP estimation represents one of most promising approaches, its use in daily life is limited owing to the requirement of multi systems to measure PTT, and its performance in systolic blood pressure (SBP) estimation is not yet satisfactory. The first goal of this study is to develop a wearable system providing convenient measurement of the PTT, which facilitates continuous BP monitoring based on PTT in daily life. A single chest-worn device was developed measuring a photoplethysmogram (PPG) and a seismocardiogram (SCG) simultaneously, thereby obtaining PTT by using the SCG as timing reference of the aortic valve opening and the PPG as timing reference of pulse arrival. The presented device was designed to be compact and convenient to use, and to last for 24h by reducing power consumption of the system. The consistency of BP related parameters extracted from the system including PTT between repetitive measurements was verified by an intra-class correlation analysis, and it was over 0.8 for all parameters. In addition, the use of SCG as timing reference of the aortic valve opening was verified by comparing it with an impedance cardiogram (r = 0.79 ± 0.14). Secondly, the algorithm improving the performance of the SBP estimation was developed by using the presented system. A multivariate model using SCG amplitude (SA) in conjunction with PTT was proposed for SBP estimation, and was compared with conventional models using only PTT or pulse arrival time (PAT) in various interventions inducing BP changes. Furthermore, we validated the proposed model against the general population with a simple calibration process and verified its potential for daily use. The results suggested that (1) the proposed model, which employed SA in conjunction with PTT for SBP estimation, outperformed the conventional univariate model using PTT or PAT (the mean absolute errors were of 4.57, 6.01, and 6.11 for the proposed, PTT, and PAT models, respectively)(2) for practical use, the proposed model showed potential to be generalized with a simple calibrationand (3) the proposed model and system demonstrated the potential for continuous BP monitoring in daily life without any intervention of users or regulations. In conclusion, the presented system provides an improved performance of continuous BP monitoring in daily life by using a combination of PTT and SA with a convenient and compact single chest-worn device, and thus, it can contribute to mobile healthcare services.CONTENTS Abstract i Contents v List of Tables ix List of Figures xi List of Abbreviations xvi Chapter 1 1 General Introduction 1.1. Blood pressure 2 1.2. Pulse transit time 6 1.3. Thesis objective 12 Chapter 2 14 Development of the Wearable Blood Pressure Monitoring System 2.1. Introduction 15 2.2. System overview 17 2.3. Bio-signal instrumentation 21 2.4. Power management 24 2.5. PCB and case design 25 2.6. Software Design 27 2.7. Signal Processing 30 2.8. Experimental setup 34 2.8.1. Repeatability test 34 2.8.2. Verification of SCG-based PEP 35 2.9. Results and Discussion 38 2.9.1. Repeatability test 38 2.9.2. Verification of SCG-based PEP 40 Chapter 3 43 Enhancement of PTT based BP estimation 3.1. Introduction 44 3.2. Method 47 3.2.1. Principle of BP estimation 47 3.2.2. Subjects 49 3.2.3. Study protocol 50 3.2.4. Data collection 56 3.2.5. Data analysis 60 3.2.6. Evaluation standard 64 3.3. Results 67 3.4. Discussion 96 Chapter 4 113 Conclusion 4.1. Thesis Summary and Contributions 114 4.2. Future Direction 116 Bibliography 118 Abstract in Korean 128Docto

Mobile Personal Healthcare System for Non-Invasive, Pervasive and Continuous Blood Pressure Monitoring: A Feasibility Study

Background: Smartphone-based blood pressure (BP) monitor using photoplethysmogram (PPG) technology has emerged as a promising approach to empower users with self-monitoring for effective diagnosis and control ofhypertension (HT). Objective: This study aimed to develop a mobile personal healthcare system for non-invasive, pervasive, and continuous estimation of BP level and variability to be user-friendly to elderly. Methods: The proposed approach was integrated by a self-designed cuffless, calibration-free, wireless and wearable PPG-only sensor, and a native purposely-designed smartphone application using multilayer perceptron machine learning techniques from raw signals. We performed a pilot study with three elder adults (mean age 61.3 ± 1.5 years; 66% women) to test usability and accuracy of the smartphone-based BP monitor. Results: The employed artificial neural network (ANN) model performed with high accuracy in terms of predicting the reference BP values of our validation sample (n=150). On average, our approach predicted BP measures with accuracy \u3e90% and correlations \u3e0.90 (P \u3c .0001). Bland-Altman plots showed that most of the errors for BP prediction were less than 10 mmHg. Conclusions: With further development and validation, the proposed system could provide a cost-effective strategy to improve the quality and coverage of healthcare, particularly in rural zones, areas lacking physicians, and solitary elderly populations

Cuffless Single-Site Photoplethysmography for Blood Pressure Monitoring

One in three adults worldwide has hypertension, which is associated with significant morbidity and mortality. Consequently, there is a global demand for continuous and non-invasive blood pressure (BP) measurements that are convenient, easy to use, and more accurate than the currently available methods for detecting hypertension. This could easily be achieved through the integration of single-site photoplethysmography (PPG) readings into wearable devices, although improved reliability and an understanding of BP estimation accuracy are essential. This review paper focuses on understanding the features of PPG associated with BP and examines the development of this technology over the 2010-2019 period in terms of validation, sample size, diversity of subjects, and datasets used. Challenges and opportunities to move single-site PPG forward are also discussed