Post-exercise contractility, diastolic function, and pressure: Operator-independent sensor-based intelligent monitoring for heart failure telemedicine
© Bombardini et al; licensee BioMed Central Ltd. 2009
Received: 09 April 2009
Accepted: 14 May 2009
Published: 14 May 2009
New sensors for intelligent remote monitoring of the heart should be developed. Recently, a cutaneous force-frequency relation recording system has been validated based on heart sound amplitude and timing variations at increasing heart rates.
To assess sensor-based post-exercise contractility, diastolic function and pressure in normal and diseased hearts as a model of a wireless telemedicine system.
We enrolled 150 patients and 22 controls referred for exercise-stress echocardiography, age 55 ± 18 years. The sensor was attached in the precordial region by an ECG electrode. Stress and recovery contractility were derived by first heart sound amplitude vibration changes; diastolic times were acquired continuously. Systemic pressure changes were quantitatively documented by second heart sound recording.
Interpretable sensor recordings were obtained in all patients (feasibility = 100%). Post-exercise contractility overshoot (defined as increase > 10% of recovery contractility vs exercise value) was more frequent in patients than controls (27% vs 8%, p < 0.05). At 100 bpm stress heart rate, systolic/diastolic time ratio (normal, < 1) was > 1 in 20 patients and in none of the controls (p < 0.01); at recovery systolic/diastolic ratio was > 1 in only 3 patients (p < 0.01 vs stress). Post-exercise reduced arterial pressure was sensed.
Post-exercise contractility, diastolic time and pressure changes can be continuously measured by a cutaneous sensor. Heart disease affects not only exercise systolic performance, but also post-exercise recovery, diastolic time intervals and blood pressure changes – in our study, all of these were monitored by a non-invasive wearable sensor.
Telemonitoring heart failure patients is a very promising way of managing several complex and costly healthcare issues . Recent European Society of Cardiology (ESC) guidelines on heart failure do recommend developing management programs for recently hospitalized patients with HF . Screening left ventricular dysfunction would be very important, since heart failure is associated with high morbidity, mortality, and cost. Therefore, there is a great need for the design and implementation of an interactive real-time wireless telemedicine system . Non-invasive new sensors for intelligent remote cardiac monitoring should be developed and integrated with other standard physiological sensor and biomarkers.
A new cutaneous force-frequency relation recording system has recently been validated in the stress echo lab, based on heart sound amplitude and timing variations at increasing heart rates. Expert monitoring of the heart – via a chest wall accelerometer – can reliably and non-invasively sense the contractile force and the filling function of the heart [4–6].
Information obtained from the ECG (QRS detector) and the heart sound vibration (HSV peak detector): heart rate, first heart sound and second heart sound, are analyzed by algorithms in order to derive the systolic force-frequency relation and the diastolic force-frequency relation. The physiological backgrounds are: 1) The systolic force-frequency relation. An increased heart rate progressively increases the contractile force of the heart . In humans, an increase in heart rate from 60 to 170 bpm stimulates developed force. If chronic heart failure and/or myopathic, valvulopathic or ischemic cardiomyopathy is present, this intrinsic property of the myocardium is partially or totally depressed, because of which the contractile force decreases for cardiac frequencies of the order of 100 bpm or even lower . 2) The diastolic force-frequency relation. If chronic heart failure is present, the decompensated myocardium undergoes a phenotypic change with activity alteration of the enzymes which regulate calcium homeostasis: diastolic uptake of calcium decreases and contractile performance improves only with bradycardia .
The daily life of both healthy subjects and patients involves periods of rest alternating with physical activity ; and activity consists of mild to strenuous exercise with obviously subsequent recovery periods. Testing this new sensor in the post-exercise period is mandatory before its application in telemedicine systems for close and continuous monitoring of heart failure in daily life.
The aims of this study were (1) to compare the sensor-based quantification with standard stress echo assessment in the post-exercise phase and (2) to exploit the sensor-based intelligent monitoring in a larger group of exercising subjects as a model of a wireless telemedicine system.
40 ± 13
61 ± 8
CAD (no MI)
65 ± 8
62 ± 8
CHD (previous MI)
64 ± 9
50 ± 14
68 ± 9
39 ± 8
60 ± 7
61 ± 9
62 ± 12
61 ± 3
59 ± 15
60 ± 11
28 ± 14
46 ± 32
48 ± 16
58 ± 10
Semi-supine bicycle exercise
Graded semi-supine bicycle exercise echo was performed, starting at an initial workload of 25 watts lasting for 2 min; thereafter the workload was increased stepwise by 25 watts at 2-min intervals. A 12-lead electrocardiogram and blood pressure measurement were performed at baseline and every minute thereafter . Two-dimensional echocardiographic monitoring was performed throughout and up to 5 min after the end of stress.
Regional wall motion analysis
Regional wall motion analysis was evaluated at baseline and at peak stress with a semiquantitative assessment of a wall motion score index (WMSI), with the 17-segment model of the left ventricle, each segment ranging from 1 = normal/hyperkinetic to 4 = dyskinetic, according to the recommendations of the European and of the American Society of Echocardiography [13, 14]. WMSI was derived by dividing the sum of individual segment scores by the number of interpretable segments [10, 13]. Test positivity was defined as the occurrence of at least one of the following conditions: 1) new dyssynergy in a region with normal rest function (i.e. normokinesia becoming hypokinesia, akinesia or dyskinesia) in at least two adjacent segments [15, 16]; 2) worsening of a resting dissynergy.
Diagnostic end points and interruption criteria
The diagnostic end-points were the development of obvious echocardiography positivity. The test was also stopped, in the absence of diagnostic endpoints, for one of the following reasons for performing a submaximal, non-diagnostic test: intolerable symptoms, limiting asymptomatic side effects consisting of (a) hypertension (systolic blood pressure > 220 mmHg; diastolic blood pressure > 120 mmHg) (b) relative or absolute hypotension (> 30 mmHg fall in blood pressure), (c) supraventricular arrhythmias: supraventricular tachycardia or atrial fibrillation, (d) ventricular arrhythmias: ventricular tachycardia; frequent, polymorphous premature ventricular beats .
Blood pressure analysis
One nurse recorded blood pressures of each patient at rest and during the study. The blood pressure recording was made using a sphygmomanometer and the diaphragm of a standard stethoscope . Systolic and diastolic blood pressure was measured in the right arm. During exercise test and recovery, blood pressure was recorded with the patient lying in a left-rotated semi-supine position and gripping the left support with their left hand. Patients were told to let their right hand go limp when blood pressure was measured. Post-exercise hypotension was defined as at least 5 mmHg of diastolic blood pressure reduction vs the same exercise heart rate values .
Echocardiographic hemodynamic assessment
Quantitative stress-echo assessment and calculated hemodynamic parameters
Measured values (rest, peak stress, recovery min. 1, 3, 5)
LV ESV index
2D echo (Simpson rule)/BSA
LV EDV index
2D echo (Simpson rule)/BSA
(rest, peak stress, recovery min. 1, 3, 5)
Stroke volume index
EDV index – ESV index
stroke volume index * heart rate
Mean Arterial Pressure
(SBP-DBP)/3 + DBP
LV elastance index
Effective arterial elastance index (EaI)
(SBP*0.9)/Stroke volume index
LV elastance index/Eai
80 * (MAP-5)/Cardiac index
dyne * sec * cm 5
Contractility, diastolic time, and arterial pressure measurements by precordial cutaneous sensor
Sensor-based intelligent monitoring as a model of a wireless telemedicine system
The systolic force-frequency relation, the diastolic time-frequency relation and the second heart sound derived systemic pressure were recorded at both stress and recovery in the 172 recruited subjects to exploit sensor-based dichotomy patterns in the leap to non-invasive intelligent remote heart monitoring.
SPSS 11 for Windows was used for statistical analysis. The statistical analyses included descriptive statistics (frequency and percentage of categorical variables and mean and standard deviation of continuous variables). Since we observed large differences in baseline sensor-derived systolic force and S2 vibration amplitude, % changes were assessed during stress and recovery for interpatient and intergroup comparisons. Diastolic times were measured as absolute values simultaneously with systolic/diastolic time ratio. Chi-square test was used for comparisons between echo and sensor based contractility overshoot assessment (yes/no) and reduced pressure (yes/no) in the post- exercise phase. Changes in continuous variables during recovery were compared by analysis of variance for repeated measures. When this test was significant, individual comparisons of end-exercise value (recovery time = 0) and values during 1, 3 and 5 min of recovery were made by Duncan's multiple-range test. Since all the sensor-based parameters are physiologically heart-rate dependent, comparisons of recovery minutes 1, 3 and 5 values were made with sensor-recorded values at the same heart rates during exercise. A p-value < 0.05 was accepted as statistically significant.
Stress echo results
Exercise time was 11 ± 5 min in the 22 controls and 9 ± 3 min in the 150 patients. WMSI was 1 at rest = peak stress in the 22 controls and 1.17 ± 0.35 at rest, 1.18 ± 0.37 peak stress in the 150 patients. Four patients had stress-induced ischemia (WMSI rest = 1.36 ± 0.35, peak = 1.77 ± 0.31).
Comparison between sensor and echo assessment in 52 subjects
Sensor-based force-frequency relation, diastolic time-frequency relation and derived systemic pressure in the post-exercise phase in the 172 enrolled subjects
The post-exercise force frequency relation and the contractile overshoot
Diastolic time-frequency relation and the post-exercise diastolic time overshoot
Sensor-derived systemic pressure and post-exercise hypotension
Comparisons between sensor- and echo-derived information on function during recovery
At force-frequency analysis, with both computed elastance (SP/ESV index) and operator-independent sensor (FHS vibrations amplitude) most patients showed a contractility increase at recovery. Standard systemic pressure measures (obtained by sphygmomanometer) were blunted in the post-exercise phase, and a general decrease in the sensor-based derived systemic pressure were found . Furthermore, during recovery as during stress, the cutaneous operator-independent force sensor described systolic and diastolic duration in real time. Simultaneous calculation of stroke volume with echo and diastolic time with force sensor allowed us to monitor the diastolic filling rate .
Sensor-based post-exercise force-frequency relation in normal and diseased hearts
During exercise the normal force-frequency relation is upsloping, while a flat-biphasic force-frequency relation is abnormal [20–24]. A post-exercise sensor-based contractility overshoot was more frequent in patients vs controls, and frequently associated with an abnormal blunted force-frequency relation during exercise. Several investigators using different methods [12, 25–27] have reported an overshoot of cardiac function during recovery from maximal exercise in patients with cardiac disease. Koike et al.  have shown a marked rebound of stroke volume immediately after cessation of upright exercise in patients with previous myocardial infarction. Tanabe at al.  found an overshoot of cardiac output at 1 min of recovery in patients with severe CHF, along with poor cardiac output response to exercise. They found that not only O2 uptake but also cardiac output fell much more slowly after maximal exercise as CHF worsened. Although insufficient afterload reduction during exercise in CHF contributes to the impaired stroke volume response to exercise, systemic vascular resistance at 1 min of recovery significantly decreased from that at peak exercise in patients with CHF who showed overshoot of cardiac output during recovery [28–31]. The marked increase in stroke volume during early recovery in patients with overshoot appears to result from both an immediate afterload reduction and a relatively slow decrease in cardiac sympathetic stimulation during recovery [32, 33]. Knowledge of the post-exercise overshoot also had prognostic value since patients with a moderate exercise intolerance and a normal recovery period had a better prognosis than a patient with a post-exercise overshoot .
Sensor-based diastolic time-frequency relation in the post-exercise
We found that at each recovery heart beat frequency, the diastolic time was higher than the diastolic time recorded during exercise, in both controls and patients. Why does diastolic time increase in the post- exercise phase? The total cardiac cycle duration is algebraically dependent on the heart rate [= 60,000 msec/heart rate] . However at each heartbeat frequency the fixed total cardiac cycle time can be differently divided between systole and diastole . The diastolic time fraction is determined by factors that modulate systolic duration through modulation of myocyte contraction [36–40]. At recovery, improved myocardial contractility and reduction in systemic vascular resistance significantly shortened left ventricular ejection time, with a proportionate increase in diastolic time fraction. Stress-induced "systolic-diastolic mismatch" can be easily quantified by a disproportionate decrease in diastolic time fraction, and is associated with several cardiac diseases, possibly expanding the spectrum of information obtainable during stress . The post-exercise diastolic time fraction indicates the duration of absence of compression of intramural vessels during a heartbeat and has a dominant role in the subendocardial layer – whose perfusion is mainly diastolic, whereas the perfusion in the subepicardial layer is also systolic [36, 38]. The lengthening of cardiological diastole is much more pronounced than lengthening of cardiological systole, and the former is much more effective for subendocardial perfusion, even in the absence of coronary artery disease. This indicates the relevance of monitoring both exercise and recovery diastolic time in the critically diseased heart [37, 39].
Systemic pressure in the post-exercise phase and sensor-monitored pressure changes
A significant correlation was found between post-exercise hypotension and recovery S2 undershoot (Fig. 9). In this investigation, blood pressure (systolic, diastolic and mean) correlated closely with S2 amplitude during both stress and recovery . This could be explained by the fact that amplitude is primarily determined by one factor, the force of valve closure [41, 42]. In the selected patients of our study, a significant correlation was found between post-exercise hypotension and recovery second heart sound lower amplitude, to confirm the sensor's ability to mirror the diastolic pressure trend. Post-exercise hypotension has been demonstrated in both hypertensive and healthy subjects , and it has been attributed to a decrease in cardiac output and/or systemic vascular resistance [44–47]. Acute exercise may serve as a non-pharmacological aid in the treatment of hypertension. S2 amplitude monitoring could be a method for assessing the efficacy of acute post-exercise blood pressure reduction.
Clinical implications, implantable vs. wearable sensors and chronic heart failure
Congestive heart failure (HF) is a serious public health problem due to its prevalence, high mortality, high morbidity, and the expense of ongoing therapy .
Several strategies to control fluid volume status are used in the practice. Clinic visits for assessment of filling pressure by physical examination, multiple types of non-invasive measurements, and repeated cardiac catheterization may be employed. There is considerable cost and inconvenience for the patient associated with these strategies and, more importantly, these methods represent pressure and volume status only as one discrete point in time without the perturbance of daily activities or stress. A system of frequent monitoring could alert clinicians to early signs and symptoms of decompensation, providing the opportunity for intervention before patients become severely ill and require hospitalization .
Implantable hemodynamic monitors (IHMO)
Implantable hemodynamic monitors that are capable of measuring chronic right ventricular oxygen saturation and pulmonary artery pressure are currently being developed (Chronicle, Medtronic Inc. Minneapolis, Minnesota, USA) .
Cardiac resynchronization therapy/defibrillators and implantable cardioverter defibrillators with continuous intrathoracic impedance monitoring capabilities (OptiVol fluid status monitoring; Medtronic Inc. Minneapolis, Minnesota, USA) have recently been introduced and may provide an early warning of thoracic fluid retention . However the predictive values of these implantable devices is still unknown [48, 49]. Furthermore, such strategies will have to be evaluated for cost effectiveness, scalability, safety, and acceptability to patients.
As technologies such as micro-technologies, telecommunication, low-power design, new textiles, and flexible sensors become available, new user-friendly devices can be developed to enhance the comfort and security of the patient. Since clothes and textiles are in direct contact with about 90% of the skin surface, smart sensors and smart clothes with non-invasive sensors are an attractive solution for home-based and ambulatory health monitoring . All these systems can provide a safe and comfortable environment for home healthcare, preventive medicine, and public health.
The systolic and diastolic FFR sensor
Sensor-monitored force-frequency relation in normal and diseased hearts
Force-Frequency Relation (FFR)
Diastolic time-frequency relation
systolic/diastolic time ratio < 1
Acute biphasic FFR
Acute systolic/diastolic time ratio > 1
Acute S2 blunting
CHF worsening ↓
1- Blunted FFR slope
2- From upsloping to biphasic FFR
Systolic/diastolic time ratio > 1 at lower HR
3- Lower critical HR in biphasic FFR
- Recovery overshoot
CHF improving ↑↑↑
3- Upsloping FFR
2- From biphasic to upsloping FFR
Systolic/diastolic time ratio > 1 at higher HR
1- Higher critical HR in biphasic FFR
- Normal recovery
Systolic/diastolic time ratio > 1 at lower HR
Steeper S2 curve
Preceding and pre-preceding interval FFR dependence
Systolic/diastolic time ratio scattering
Our research will continue to optimize features of both the sensor and algorithm, and will develop an engineering model for industrialization, aiming at the device's eventual use in long-term home monitoring for tailoring drug treatment and preventing re-hospitalization.
Contractility can be continuously measured by a cutaneous accelerometer during the post-exercise phase. Knowledge of the recovery overshoot phenomenon could be helpful for recognizing advanced failing patients in home monitoring systems. Diastolic duration time can be monitored during the post-exercise phase and a recovery diastolic time overshoot phenomenon can be easily assessed by the sensor. S2 amplitude monitoring is a method for assessing acute post-exercise blood pressure reduction. The daily life of both healthy subjects and patients involves periods of rest alternating with physical activity; and activity consists of mild to severe exercise with obviously subsequent recovery periods. Heart disease affects not only peak exercise systolic performance, but also post-exercise recovery, diastolic time intervals and blood pressure changes – all of which can be monitored by a non-invasive wearable sensor.
body surface area
diastolic blood pressure
coronary artery disease
congestive heart failure
idiopathic dilated cardiomyopathy
effective arterial elastance index
first heart sound
- g :
acceleration unit (9.8 m/sec2)
implantable hemodynamic monitor
second heart sound
systolic blood pressure
systemic vascular resistance
wall motion score index
Publication cost has been funded by: Prof. Giorgio Arpesella, Director, Heart Transplant Unit, Bologna University, Department of Cardiac Surgery, Heart and Lung Transplantation Program, Policlinico S. Orsola, Via Massarenti, 9
40138 Bologna, Italy.
We are grateful to Alison Frank for copyediting/proofreading the English in this manuscript.
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