David B. Camarillo is Assistant Professor of Bioengineering, (by courtesy) Mechanical Engineering and Neurosurgery at Stanford University. Dr. Camarillo holds a B.S.E in Mechanical and Aerospace Engineering from Princeton University, a Ph.D. in Mechanical Engineering from Stanford University and completed postdoctoral fellowships in Biophysics at the UCSF and Biodesign Innovation at Stanford. Dr. Camarillo worked in the surgical robotics industry at Intuitive Surgical and Hansen Medical, before launching his laboratory at Stanford in 2012. His current research focuses on precision human measurement for multiple clinical and physiological areas including the brain, heart, lungs, and reproductive system. Dr. Camarillo has been awarded the Hellman Fellowship, the Office of Naval Research Young Investigator Program award, among other honors including multiple best paper awards in brain injury and robotic surgery. His research has been funded by the NIH, NSF, DoD, as well as corporations and private philanthropy. His lab’s research has been featured on NPR, the New York Times, The Washington Post, Science News, ESPN, and TED.com as well as other media outlets aimed at education of the public.
Boards, Advisory Committees, Professional Organizations
Member, Program in Biodesign (2012 - Present)
Member, Biomedical Engineering Society (BMES) (2014 - Present)
Member, National Neurotrauma Society (NNS) (2014 - Present)
Member, American Society of Mechanical Engineers (ASME) (2012 - Present)
Member, Institute of Electrical and Electronics Engineers (IEEE) (2005 - Present)
PhD, Stanford University, Mechanical Engineering (2008)
BSE, Princeton, Mechanical and Aerospace Engineering (2001)
Correlation Between Oocyte and Embryo Mechanical Properties on Embryo Development and Clinical Pregnancy After In Vitro Fertilization
The purpose of this study is to determine whether oocyte and embryo mechanical properties measured during in vitro fertilization can predict embryo development outcomes and clinical pregnancy.
- Senior Capstone Design I
BIOE 141A (Aut)
- Senior Capstone Design II
BIOE 141B (Win)
Independent Studies (10)
- Bioengineering Problems and Experimental Investigation
BIOE 191 (Aut, Win, Spr, Sum)
- Directed Investigation
BIOE 392 (Aut, Win, Spr, Sum)
- Directed Study
BIOE 391 (Aut, Win, Spr, Sum)
- Engineering Problems
ME 391 (Aut, Win, Spr, Sum)
- Engineering Problems and Experimental Investigation
ME 191 (Aut, Win, Spr, Sum)
- Experimental Investigation of Engineering Problems
ME 392 (Aut, Win, Spr, Sum)
- Honors Research
ME 191H (Aut, Win, Spr, Sum)
- Ph.D. Teaching Experience
ME 491 (Aut, Win, Spr, Sum)
- Practical Training
ME 299A (Aut, Win, Spr, Sum)
- Practical Training
ME 299B (Aut, Win, Spr, Sum)
- Bioengineering Problems and Experimental Investigation
- Prior Year Courses
Head Impact Kinematics Estimation With Network of Inertial Measurement Units.
Journal of biomechanical engineering
2018; 140 (9)
Wearable sensors embedded with inertial measurement units have become commonplace for the measurement of head impact biomechanics, but individual systems often suffer from a lack of measurement fidelity. While some researchers have focused on developing highly accurate, single sensor systems, we have taken a parallel approach in investigating optimal estimation techniques with multiple noisy sensors. In this work, we present a sensor network methodology that utilizes multiple skin patch sensors arranged on the head and combines their data to obtain a more accurate estimate than any individual sensor in the network. Our methodology visually localizes subject-specific sensor transformations, and based on rigid body assumptions, applies estimation algorithms to obtain a minimum mean squared error estimate. During mild soccer headers, individual skin patch sensors had over 100% error in peak angular velocity magnitude, angular acceleration magnitude, and linear acceleration magnitude. However, when properly networked using our visual localization and estimation methodology, we obtained kinematic estimates with median errors below 20%. While we demonstrate this methodology with skin patch sensors in mild soccer head impacts, the formulation can be generally applied to any dynamic scenario, such as measurement of cadaver head impact dynamics using arbitrarily placed sensors.
View details for DOI 10.1115/1.4039987
View details for PubMedID 29801166
- Comparison of video-based and sensor-based head impact exposure PLOS ONE 2018; 13 (6)
Spinal constraint modulates head instantaneous center of rotation and dictates head angular motion.
Journal of biomechanics
The head is kinematically constrained to the torso through the spine and thus, the spine dictates the amount of output head angular motion expected from an input impact. Here, we investigate the spinal kinematic constraint by analyzing the head instantaneous center of rotation (HICOR) with respect to the torso in head/neck sagittal extension and coronal lateral flexion during mild loads applied to 10 subjects. We found the mean HICOR location was near the C5-C6 intervertebral joint in sagittal extension, and T2-T3 intervertebral joint in coronal lateral flexion. Using the impulse-momentum relationship normalized by subject mass and neck length, we developed a non-dimensional analytical ratio between output angular velocity and input linear impulse as a function of HICOR location. The ratio was 0.65 and 0.50 in sagittal extension and coronal lateral flexion respectively, implying 30% greater angular velocities in sagittal extension given an equivalent impulse. Scaling to subject physiology also predicts larger required impulses given greater subject mass and neck length to achieve equivalent angular velocities, which was observed experimentally. Furthermore, the HICOR has greater motion in sagittal extension than coronal lateral flexion, suggesting the head and spine can be represented with a single inverted pendulum in coronal lateral flexion, but requires a more complex representation in sagittal extension. The upper cervical spine has substantial compliance in sagittal extension, and may be responsible for the complex motion and greater extension angular velocities. In analyzing the HICOR, we can gain intuition regarding the neck's role in dictating head motion during external loading.
View details for DOI 10.1016/j.jbiomech.2018.05.024
View details for PubMedID 29929891
Voluntary Head Rotational Velocity and Implications for Brain Injury Risk Metrics.
Journal of neurotrauma
We investigated whether humans could sustain high head rotational velocities without brain injury. Rotational velocity has long been implicated for predicting concussion risk, and has recently been used to develop the rotational velocity-based Brain Injury Criterion (BrIC). To assess the efficacy of rotational velocity and BrIC for predicting concussion risk, we instrumented 9 male subjects with sensor-laden mouthguards and measured six-degree-of-freedom head accelerations for 27 rapid voluntary head rotations. The fastest rotations produced peak rotational velocities of 12.6 rad/s, 17.4 rad/s, and 25.0 rad/s in the coronal, sagittal, and horizontal planes, respectively. All of these exceeded the corresponding medians from padded sports impacts (8.9 rad/s, 10.7 rad/s, and 8.4 rad/s, respectively), and in the case of sagittal and horizontal rotation, were within 1 standard deviation of published concussion averages. In the horizontal plane, 4 voluntary rotations exceeded the concussive impact median BrIC. The area under the precision-recall curve was lower in BrIC (0.49) than just using horizontal rotational acceleration (0.8), which distinguished concussive and subconcussive motions better. Voluntary motions produced less than 4% max principal strain (MPS) in finite element simulation, 5 times below predictions from dummy impacts used to develop BrIC. Despite having the highest critical velocity in BrIC, coronal rotation produced more tract-oriented strain in the corpus callosum than other planes. Baseline and post-experiment neurological testing revealed no significant deficits. We find that the head can tolerate high-velocity, low-acceleration rotational inputs too slow to produce substantial brain deformation. These findings suggest that the time regime over which angular velocities occur must be carefully considered for concussion prediction.
View details for DOI 10.1089/neu.2016.4758
View details for PubMedID 29848152
- Validation of a Custom Instrumented Retainer Form Factor for Measuring Linear and Angular Head Impact Kinematics JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME 2018; 140 (5)
Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis
PHYSICAL REVIEW LETTERS
2018; 120 (13): 138101
Although concussion is one of the greatest health challenges today, our physical understanding of the cause of injury is limited. In this Letter, we simulated football head impacts in a finite element model and extracted the most dominant modal behavior of the brain's deformation. We showed that the brain's deformation is most sensitive in low frequency regimes close to 30 Hz, and discovered that for most subconcussive head impacts, the dynamics of brain deformation is dominated by a single global mode. In this Letter, we show the existence of localized modes and multimodal behavior in the brain as a hyperviscoelastic medium. This dynamical phenomenon leads to strain concentration patterns, particularly in deep brain regions, which is consistent with reported concussion pathology.
View details for DOI 10.1103/PhysRevLett.120.138101
View details for Web of Science ID 000428783300021
View details for PubMedID 29694192
Propagation of errors from skull kinematic measurements to finite element tissue responses
BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
2018; 17 (1): 235–47
Real-time quantification of head impacts using wearable sensors is an appealing approach to assess concussion risk. Traditionally, sensors were evaluated for accurately measuring peak resultant skull accelerations and velocities. With growing interest in utilizing model-estimated tissue responses for injury prediction, it is important to evaluate sensor accuracy in estimating tissue response as well. Here, we quantify how sensor kinematic measurement errors can propagate into tissue response errors. Using previous instrumented mouthguard validation datasets, we found that skull kinematic measurement errors in both magnitude and direction lead to errors in tissue response magnitude and distribution. For molar design instrumented mouthguards susceptible to mandible disturbances, 150-400% error in skull kinematic measurements resulted in 100% error in regional peak tissue response. With an improved incisor design mitigating mandible disturbances, errors in skull kinematics were reduced to <50%, and several tissue response errors were reduced to <10%. Applying 30[Formula: see text] rotations to reference kinematic signals to emulate sensor transformation errors yielded below 10% error in regional peak tissue response; however, up to 20% error was observed in peak tissue response for individual finite elements. These findings demonstrate that kinematic resultant errors result in regional peak tissue response errors, while kinematic directionality errors result in tissue response distribution errors. This highlights the need to account for both kinematic magnitude and direction errors and accurately determine transformations between sensors and the skull.
View details for DOI 10.1007/s10237-017-0957-8
View details for Web of Science ID 000424651600017
View details for PubMedID 28856485
View details for PubMedCentralID PMC5809213
Comparison of video-based and sensor-based head impact exposure.
2018; 13 (6): e0199238
Previous research has sought to quantify head impact exposure using wearable kinematic sensors. However, many sensors suffer from poor accuracy in estimating impact kinematics and count, motivating the need for additional independent impact exposure quantification for comparison. Here, we equipped seven collegiate American football players with instrumented mouthguards, and video recorded practices and games to compare video-based and sensor-based exposure rates and impact location distributions. Over 50 player-hours, we identified 271 helmet contact periods in video, while the instrumented mouthguard sensor recorded 2,032 discrete head impacts. Matching video and mouthguard real-time stamps yielded 193 video-identified helmet contact periods and 217 sensor-recorded impacts. To compare impact locations, we binned matched impacts into frontal, rear, side, oblique, and top locations based on video observations and sensor kinematics. While both video-based and sensor-based methods found similar location distributions, our best method utilizing integrated linear and angular position only correctly predicted 81 of 217 impacts. Finally, based on the activity timeline from video assessment, we also developed a new exposure metric unique to American football quantifying number of cross-verified sensor impacts per player-play. We found significantly higher exposure during games (0.35, 95% CI: 0.29-0.42) than practices (0.20, 95% CI: 0.17-0.23) (p<0.05). In the traditional impacts per player-hour metric, we observed higher exposure during practices (4.7) than games (3.7) due to increased player activity in practices. Thus, our exposure metric accounts for variability in on-field participation. While both video-based and sensor-based exposure datasets have limitations, they can complement one another to provide more confidence in exposure statistics.
View details for DOI 10.1371/journal.pone.0199238
View details for PubMedID 29920559
Detection of American Football Head Impacts Using Biomechanical Features and Support Vector Machine Classification.
2017; 8 (1): 855
Accumulation of head impacts may contribute to acute and long-term brain trauma. Wearable sensors can measure impact exposure, yet current sensors do not have validated impact detection methods for accurate exposure monitoring. Here we demonstrate a head impact detection method that can be implemented on a wearable sensor for detecting field football head impacts. Our method incorporates a support vector machine classifier that uses biomechanical features from the time domain and frequency domain, as well as model predictions of head-neck motions. The classifier was trained and validated using instrumented mouthguard data from collegiate football games and practices, with ground truth data labels established from video review. We found that low frequency power spectral density and wavelet transform features (10~30Hz) were the best performing features. From forward feature selection, fewer than ten features optimized classifier performance, achieving 87.2% sensitivity and 93.2% precision in cross-validation on the collegiate dataset (n=387), and over 90% sensitivity and precision on an independent youth dataset (n=32). Accurate head impact detection is essential for studying and monitoring head impact exposure on the field, and the approach in the current paper may help to improve impact detection performance on wearable sensors.
View details for DOI 10.1038/s41598-017-17864-3
View details for PubMedID 29321637
Pilot Findings of Brain Displacements and Deformations during Roller Coaster Rides
JOURNAL OF NEUROTRAUMA
2017; 34 (22): 3198–3205
With 300,000,000 riders annually, roller coasters are a popular recreational activity. Although the number of roller coaster injuries is relatively low, the precise effect of roller coaster rides on our brains remains unknown. Here we present the quantitative characterization of brain displacements and deformations during roller coaster rides. For two healthy adult male subjects, we recorded head accelerations during three representative rides, and, for comparison, during running and soccer headers. From the recordings, we simulated brain displacements and deformations using rigid body dynamics and finite element analyses. Our findings show that despite having lower linear accelerations than sports head impacts, roller coasters may lead to brain displacements and strains comparable to mild soccer headers. The peak change in angular velocity on the rides was 9.9 rad/sec, which was higher than the 5.6 rad/sec in soccer headers with ball velocities reaching 7 m/sec. Maximum brain surface displacements of 4.0 mm and maximum principal strains of 7.6% were higher than in running and similar to soccer headers, but below the reported average concussion strain. Brain strain rates during roller coaster rides were similar to those in running, and lower than those in soccer headers. Strikingly, on the same ride and at a similar position, the two subjects experienced significantly different head kinematics and brain deformation. These results indicate that head motion and brain deformation during roller coaster rides are highly sensitive to individual subjects. Although our study suggests that roller coaster rides do not present an immediate risk of acute brain injury, their long-term effects require further longitudinal study.
View details for DOI 10.1089/neu.2016.4893
View details for Web of Science ID 000414560000016
View details for PubMedID 28683585
Performance Evaluation of a Pre-computed Brain Response Atlas in Dummy Head Impacts
ANNALS OF BIOMEDICAL ENGINEERING
2017; 45 (10): 2437–50
A pre-computed brain response atlas (pcBRA) may have the potential to accelerate the investigation of the biomechanical mechanisms of traumatic brain injury on a large-scale. In this study, we further enhance the technique and evaluate its performance using six degree-of-freedom angular velocity profiles from dummy head impacts. Using the pcBRA to simplify profiles into acceleration-only shapes, sufficiently accurate strain estimates were obtained for impacts with a major dominating velocity peak. However, they were largely under-estimated when substantial deceleration occurred that reversed the direction of the angular velocity. For these impacts, estimation accuracy was substantially improved with a biphasic profile simplification (average correlation coefficient and linear regression slope of 0.92 ± 0.03 and 0.95 ± 0.07 for biphasic shapes, respectively, vs. 0.80 ± 0.06 and 0.80 ± 0.08 for acceleration-only shapes). Peak maximum principal strain (ɛ p) and cumulative strain damage measure (CSDM) from the estimated strains consistently correlated stronger than kinematic metrics with respect to the baseline ɛ p and CSDM from the directly simulated responses, regardless of the brain region, and by a large margin (e.g., correlation of 0.93 vs. 0.75 compared to Brain Injury Criterion (BrIC) for ɛ p in the whole-brain, and 0.91 vs. 0.47 compared to BrIC for CSDM in the corpus callosum). These findings further support the pre-computation technique for accurate, real-time strain estimation, which could be important to accelerate model-based brain injury studies in the future.
View details for DOI 10.1007/s10439-017-1888-3
View details for Web of Science ID 000411984300017
View details for PubMedID 28710533
View details for PubMedCentralID PMC5693659
- Modeling and Optimization of Airbag Helmets for Preventing Head Injuries in Bicycling ANNALS OF BIOMEDICAL ENGINEERING 2017; 45 (4): 1148-1160
- Microfluidic analysis of oocyte and embryo biomechanical properties to improve outcomes in assisted reproductive technologies MOLECULAR HUMAN REPRODUCTION 2017; 23 (4): 235-247
Microfluidic analysis of oocyte and embryo biomechanical properties to improve outcomes in assisted reproductive technologies.
Molecular human reproduction
Measurement of oocyte and embryo biomechanical properties has recently emerged as an exciting new approach to obtain a quantitative, objective estimate of developmental potential. However, many traditional methods for probing cell mechanical properties are time consuming, labor intensive and require expensive equipment. Microfluidic technology is currently making its way into many aspects of assisted reproductive technologies (ART), and is particularly well suited to measure embryo biomechanics due to the potential for robust, automated single-cell analysis at a low cost. This review will highlight microfluidic approaches to measure oocyte and embryo mechanics along with their ability to predict developmental potential and find practical application in the clinic. Although these new devices must be extensively validated before they can be integrated into the existing clinical workflow, they could eventually be used to constantly monitor oocyte and embryo developmental progress and enable more optimal decision making in ART.
View details for PubMedID 27932552
Modeling and Optimization of Airbag Helmets for Preventing Head Injuries in Bicycling.
Annals of biomedical engineering
Bicycling is the leading cause of sports-related traumatic brain injury. Most of the current bike helmets are made of expanded polystyrene (EPS) foam and ultimately designed to prevent blunt trauma, e.g., skull fracture. However, these helmets have limited effectiveness in preventing brain injuries. With the availability of high-rate micro-electrical-mechanical systems sensors and high energy density batteries, a new class of helmets, i.e., expandable helmets, can sense an impending collision and expand to protect the head. By allowing softer liner medium and larger helmet sizes, this novel approach in helmet design provides the opportunity to achieve much lower acceleration levels during collision and may reduce the risk of brain injury. In this study, we first develop theoretical frameworks to investigate impact dynamics of current EPS helmets and airbag helmets-as a form of expandable helmet design. We compared our theoretical models with anthropomorphic test dummy drop test experiments. Peak accelerations obtained from these experiments with airbag helmets achieve up to an 8-fold reduction in the risk of concussion compared to standard EPS helmets. Furthermore, we construct an optimization framework for airbag helmets to minimize concussion and severe head injury risks at different impact velocities, while avoiding excessive deformation and bottoming-out. An optimized airbag helmet with 0.12 m thickness at 72 ± 8 kPa reduces the head injury criterion (HIC) value to 190 ± 25 at 6.2 m/s head impact velocity compared to a HIC of 1300 with a standard EPS helmet. Based on a correlation with previously reported HIC values in the literature, this airbag helmet design substantially reduces the risks of severe head injury up to 9 m/s.
View details for PubMedID 27679447
Bandwidth and sample rate requirements for wearable head impact sensors
JOURNAL OF BIOMECHANICS
2016; 49 (13): 2918-2924
Wearable inertial sensors measure human head impact kinematics important to the on-going development and validation of head injury criteria. However, sensor specifications have not been scientifically justified in the context of the anticipated field impact dynamics. The objective of our study is to determine the minimum bandwidth and sample rate required to capture the impact frequency response relevant to injury. We used high-bandwidth head impact data as ground-truth measurements, and investigated the attenuation of various injury criteria at lower bandwidths. Given a 10% attenuation threshold, we determined the minimum bandwidths required to study injury criteria based on skull kinematics and brain deformation in three different model systems: helmeted cadaver (no neck), unhelmeted cadaver (no neck), and helmeted dummy impacts (with neck). We found that higher bandwidths are required for unhelmeted impacts in general and for studying strain rate injury criteria. Minimum gyroscope bandwidths of 300Hz in helmeted sports and 500Hz in unhelmeted sports are necessary to study strain rate based injury criteria. A minimum accelerometer bandwidth of 500Hz in unhelmeted sports is necessary to study most injury criteria. Current devices typically sample at 1000Hz, with gyroscope bandwidths below 200Hz, which are not always sufficient according to these requirements. With hard contact test conditions, the identified requirements may be higher than most soft contacts on the field, but should be satisfied to capture the worst contact, and often higher risk, scenarios relative to the specific sport or activity. Our findings will help establish standard guidelines for sensor choice and design in traumatic brain injury research.
View details for DOI 10.1016/j.jbiomech.2016.07.004
View details for Web of Science ID 000385472300047
View details for PubMedID 27497499
Effect of the mandible on mouthguard measurements of head kinematics
JOURNAL OF BIOMECHANICS
2016; 49 (9): 1845-1853
Wearable sensors are becoming increasingly popular for measuring head motions and detecting head impacts. Many sensors are worn on the skin or in headgear and can suffer from motion artifacts introduced by the compliance of soft tissue or decoupling of headgear from the skull. The instrumented mouthguard is designed to couple directly to the upper dentition, which is made of hard enamel and anchored in a bony socket by stiff ligaments. This gives the mouthguard superior coupling to the skull compared with other systems. However, multiple validation studies have yielded conflicting results with respect to the mouthguard׳s head kinematics measurement accuracy. Here, we demonstrate that imposing different constraints on the mandible (lower jaw) can alter mouthguard kinematic accuracy in dummy headform testing. In addition, post mortem human surrogate tests utilizing the worst-case unconstrained mandible condition yield 40% and 80% normalized root mean square error in angular velocity and angular acceleration respectively. These errors can be modeled using a simple spring-mass system in which the soft mouthguard material near the sensors acts as a spring and the mandible as a mass. However, the mouthguard can be designed to mitigate these disturbances by isolating sensors from mandible loads, improving accuracy to below 15% normalized root mean square error in all kinematic measures. Thus, while current mouthguards would suffer from measurement errors in the worst-case unconstrained mandible condition, future mouthguards should be designed to account for these disturbances and future validation testing should include unconstrained mandibles to ensure proper accuracy.
View details for DOI 10.1016/j.jbiomech.2016.04.017
View details for Web of Science ID 000377731200058
View details for PubMedID 27155744
In Vivo Evaluation of Wearable Head Impact Sensors
ANNALS OF BIOMEDICAL ENGINEERING
2016; 44 (4): 1234-1245
Inertial sensors are commonly used to measure human head motion. Some sensors have been tested with dummy or cadaver experiments with mixed results, and methods to evaluate sensors in vivo are lacking. Here we present an in vivo method using high speed video to test teeth-mounted (mouthguard), soft tissue-mounted (skin patch), and headgear-mounted (skull cap) sensors during 6-13 g sagittal soccer head impacts. Sensor coupling to the skull was quantified by displacement from an ear-canal reference. Mouthguard displacements were within video measurement error (<1 mm), while the skin patch and skull cap displaced up to 4 and 13 mm from the ear-canal reference, respectively. We used the mouthguard, which had the least displacement from skull, as the reference to assess 6-degree-of-freedom skin patch and skull cap measurements. Linear and rotational acceleration magnitudes were over-predicted by both the skin patch (with 120% NRMS error for a(mag), 290% for α(mag)) and the skull cap (320% NRMS error for a(mag), 500% for α(mag)). Such over-predictions were largely due to out-of-plane motion. To model sensor error, we found that in-plane skin patch linear acceleration in the anterior-posterior direction could be modeled by an underdamped viscoelastic system. In summary, the mouthguard showed tighter skull coupling than the other sensor mounting approaches. Furthermore, the in vivo methods presented are valuable for investigating skull acceleration sensor technologies.
View details for DOI 10.1007/s10439-015-1423-3
View details for Web of Science ID 000373741800034
View details for PubMedID 26289941
View details for PubMedCentralID PMC4761340
Human oocyte developmental potential is predicted by mechanical properties within hours after fertilization.
2016; 7: 10809-?
The causes of embryonic arrest during pre-implantation development are poorly understood. Attempts to correlate patterns of oocyte gene expression with successful embryo development have been hampered by the lack of reliable and nondestructive predictors of viability at such an early stage. Here we report that zygote viscoelastic properties can predict blastocyst formation in humans and mice within hours after fertilization, with >90% precision, 95% specificity and 75% sensitivity. We demonstrate that there are significant differences between the transcriptomes of viable and non-viable zygotes, especially in expression of genes important for oocyte maturation. In addition, we show that low-quality oocytes may undergo insufficient cortical granule release and zona-hardening, causing altered mechanics after fertilization. Our results suggest that embryo potential is largely determined by the quality and maturation of the oocyte before fertilization, and can be predicted through a minimally invasive mechanical measurement at the zygote stage.
View details for DOI 10.1038/ncomms10809
View details for PubMedID 26904963
- Human oocyte developmental potential is predicted by mechanical properties within hours after fertilization. Nature communications 2016; 7: 10809-?
Evaluation of a laboratory model of human head impact biomechanics.
Journal of biomechanics
2015; 48 (12): 3469-3477
This work describes methodology for evaluating laboratory models of head impact biomechanics. Using this methodology, we investigated: how closely does twin-wire drop testing model head rotation in American football impacts? Head rotation is believed to cause mild traumatic brain injury (mTBI) but helmet safety standards only model head translations believed to cause severe TBI. It is unknown whether laboratory head impact models in safety standards, like twin-wire drop testing, reproduce six degree-of-freedom (6DOF) head impact biomechanics that may cause mTBI. We compared 6DOF measurements of 421 American football head impacts to twin-wire drop tests at impact sites and velocities weighted to represent typical field exposure. The highest rotational velocities produced by drop testing were the 74th percentile of non-injury field impacts. For a given translational acceleration level, drop testing underestimated field rotational acceleration by 46% and rotational velocity by 72%. Primary rotational acceleration frequencies were much larger in drop tests (~100Hz) than field impacts (~10Hz). Drop testing was physically unable to produce acceleration directions common in field impacts. Initial conditions of a single field impact were highly resolved in stereo high-speed video and reconstructed in a drop test. Reconstruction results reflected aggregate trends of lower amplitude rotational velocity and higher frequency rotational acceleration in drop testing, apparently due to twin-wire constraints and the absence of a neck. These results suggest twin-wire drop testing is limited in modeling head rotation during impact, and motivate continued evaluation of head impact models to ensure helmets are tested under conditions that may cause mTBI.
View details for DOI 10.1016/j.jbiomech.2015.05.034
View details for PubMedID 26117075
Six Degree-of-Freedom Measurements of Human Mild Traumatic Brain Injury
ANNALS OF BIOMEDICAL ENGINEERING
2015; 43 (8): 1918-1934
This preliminary study investigated whether direct measurement of head rotation improves prediction of mild traumatic brain injury (mTBI). Although many studies have implicated rotation as a primary cause of mTBI, regulatory safety standards use 3 degree-of-freedom (3DOF) translation-only kinematic criteria to predict injury. Direct 6DOF measurements of human head rotation (3DOF) and translation (3DOF) have not been previously available to examine whether additional DOFs improve injury prediction. We measured head impacts in American football, boxing, and mixed martial arts using 6DOF instrumented mouthguards, and predicted clinician-diagnosed injury using 12 existing kinematic criteria and 6 existing brain finite element (FE) criteria. Among 513 measured impacts were the first two 6DOF measurements of clinically diagnosed mTBI. For this dataset, 6DOF criteria were the most predictive of injury, more than 3DOF translation-only and 3DOF rotation-only criteria. Peak principal strain in the corpus callosum, a 6DOF FE criteria, was the strongest predictor, followed by two criteria that included rotation measurements, peak rotational acceleration magnitude and Head Impact Power (HIP). These results suggest head rotation measurements may improve injury prediction. However, more 6DOF data is needed to confirm this evaluation of existing injury criteria, and to develop new criteria that considers directional sensitivity to injury.
View details for DOI 10.1007/s10439-014-1212-4
View details for Web of Science ID 000358249800018
View details for PubMedCentralID PMC4478276
Resonance of human brain under head acceleration.
Journal of the Royal Society, Interface / the Royal Society
2015; 12 (108)
Although safety standards have reduced fatal head trauma due to single severe head impacts, mild trauma from repeated head exposures may carry risks of long-term chronic changes in the brain's function and structure. To study the physical sensitivities of the brain to mild head impacts, we developed the first dynamic model of the skull-brain based on in vivo MRI data. We showed that the motion of the brain can be described by a rigid-body with constrained kinematics. We further demonstrated that skull-brain dynamics can be approximated by an under-damped system with a low-frequency resonance at around 15 Hz. Furthermore, from our previous field measurements, we found that head motions in a variety of activities, including contact sports, show a primary frequency of less than 20 Hz. This implies that typical head exposures may drive the brain dangerously close to its mechanical resonance and lead to amplified brain-skull relative motions. Our results suggest a possible cause for mild brain trauma, which could occur due to repetitive low-acceleration head oscillations in a variety of recreational and occupational activities.
View details for DOI 10.1098/rsif.2015.0331
View details for PubMedID 26063824
View details for PubMedCentralID PMC4528602
- Resonance of human brain under head acceleration. Journal of the Royal Society, Interface / the Royal Society 2015; 12 (108)
- A Head Impact Detection System Using SVM Classification and Proximity Sensing in an Instrumented Mouthguard IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2014; 61 (11): 2659-2668
- Model-Less Feedback Control of Continuum Manipulators in Constrained Environments IEEE TRANSACTIONS ON ROBOTICS 2014; 30 (4): 880-889
Multicellular architecture of malignant breast epithelia influences mechanics.
2014; 9 (8)
Cell-matrix and cell-cell mechanosensing are important in many cellular processes, particularly for epithelial cells. A crucial question, which remains unexplored, is how the mechanical microenvironment is altered as a result of changes to multicellular tissue structure during cancer progression. In this study, we investigated the influence of the multicellular tissue architecture on mechanical properties of the epithelial component of the mammary acinus. Using creep compression tests on multicellular breast epithelial structures, we found that pre-malignant acini with no lumen (MCF10AT) were significantly stiffer than normal hollow acini (MCF10A) by 60%. This difference depended on structural changes in the pre-malignant acini, as neither single cells nor normal multicellular acini tested before lumen formation exhibited these differences. To understand these differences, we simulated the deformation of the acini with different multicellular architectures and calculated their mechanical properties; our results suggest that lumen filling alone can explain the experimentally observed stiffness increase. We also simulated a single contracting cell in different multicellular architectures and found that lumen filling led to a 20% increase in the "perceived stiffness" of a single contracting cell independent of any changes to matrix mechanics. Our results suggest that lumen filling in carcinogenesis alters the mechanical microenvironment in multicellular epithelial structures, a phenotype that may cause downstream disruptions to mechanosensing.
View details for DOI 10.1371/journal.pone.0101955
View details for PubMedID 25111489
A Head Impact Detection System Using SVM Classification and Proximity Sensing in an Instrumented Mouthguard.
IEEE transactions on bio-medical engineering
Injury from blunt head impacts causes acute neurological deficits and may lead to chronic neurodegeneration. A head impact detection device can serve both as a research tool for studying head injury mechanisms and a clinical tool for real-time trauma screening. The simplest approach is an acceleration thresholding algorithm, which may falsely detect high-acceleration spurious events such as manual manipulation of the device. We designed a head impact detection system that distinguishes head impacts from non-impacts through two subsystems. First, we use infrared proximity sensing to determine if the mouthguard is worn on the teeth to filter out all offteeth events. Second, on-teeth, non-impact events are rejected using a support vector machine classifier trained on frequency domain features of linear acceleration and rotational velocity. The remaining events are classified as head impacts. In a controlled laboratory evaluation, the present system performed substantially better than a 10g acceleration threshold in head impact detection (98% sensitivity, 99.99% specificity, 99% accuracy, and 99.98% precision, compared to 92% sensitivity, 58% specificity, 65% accuracy, and 37% precision). Once adapted for field deployment by training and validation with field data, this system has the potential to effectively detect head trauma in sports, military service, and other high-risk activities.
View details for DOI 10.1109/TBME.2014.2320153
View details for PubMedID 24800918
- Model-less Feedback Control of Continuum Manipulators in Constrained Environments IEEE Transactions on Robotics 2014; 30 (4): 880-889
Outcomes from a Postgraduate Biomedical Technology Innovation Training Program: The First 12 Years of Stanford Biodesign
ANNALS OF BIOMEDICAL ENGINEERING
2013; 41 (9): 1803-1810
The Stanford Biodesign Program began in 2001 with a mission of helping to train leaders in biomedical technology innovation. A key feature of the program is a full-time postgraduate fellowship where multidisciplinary teams undergo a process of sourcing clinical needs, inventing solutions and planning for implementation of a business strategy. The program places a priority on needs identification, a formal process of selecting, researching and characterizing needs before beginning the process of inventing. Fellows and students from the program have gone on to careers that emphasize technology innovation across industry and academia. Biodesign trainees have started 26 companies within the program that have raised over $200 million and led to the creation of over 500 new jobs. More importantly, although most of these technologies are still at a very early stage, several projects have received regulatory approval and so far more than 150,000 patients have been treated by technologies invented by our trainees. This paper reviews the initial outcomes of the program and discusses lessons learned and future directions in terms of training priorities.
View details for DOI 10.1007/s10439-013-0761-2
View details for Web of Science ID 000323736800002
View details for PubMedID 23404074
An Instrumented Mouthguard for Measuring Linear and Angular Head Impact Kinematics in American Football
ANNALS OF BIOMEDICAL ENGINEERING
2013; 41 (9): 1939-1949
The purpose of this study was to evaluate a novel instrumented mouthguard as a research device for measuring head impact kinematics. To evaluate kinematic accuracy, laboratory impact testing was performed at sites on the helmet and facemask for determining how closely instrumented mouthguard data matched data from an anthropomorphic test device. Laboratory testing results showed that peak linear acceleration (r (2) = 0.96), peak angular acceleration (r (2) = 0.89), and peak angular velocity (r (2) = 0.98) measurements were highly correlated between the instrumented mouthguard and anthropomorphic test device. Normalized root-mean-square errors for impact time traces were 9.9 ± 4.4% for linear acceleration, 9.7 ± 7.0% for angular acceleration, and 10.4 ± 9.9% for angular velocity. This study demonstrates the potential of an instrumented mouthguard as a research tool for measuring in vivo impacts, which could help uncover the link between head impact kinematics and brain injury in American football.
View details for DOI 10.1007/s10439-013-0801-y
View details for Web of Science ID 000323736800015
View details for PubMedID 23604848
- An Instrumented Mouthguard for Measuring Linear and Angular Head Impact Kinematics in American Football. Annals of Biomedical Engineering 2013; 41 (9): 1939-1949
- Comparing In Vivo Head Impact Kinematics from American Football with Laboratory Drop and Linear Impactors. 2013
- Model-less Feedback Control of Continuum Manipulators in Constrained Environments. IEEE Transactions on Robotic. 2013
- Head Contacts in Collegiate Football Measured with an Instrumented Mouthguard. 2012
In Vivo Micro-Image Mosaicing
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
2011; 58 (1): 159-171
Recent advances in optical imaging have led to the development of miniature microscopes that can be brought to the patient for visualizing tissue structures in vivo. These devices have the potential to revolutionize health care by replacing tissue biopsy with in vivo pathology. One of the primary limitations of these microscopes, however, is that the constrained field of view can make image interpretation and navigation difficult. In this paper, we show that image mosaicing can be a powerful tool for widening the field of view and creating image maps of microanatomical structures. First, we present an efficient algorithm for pairwise image mosaicing that can be implemented in real time. Then, we address two of the main challenges associated with image mosaicing in medical applications: cumulative image registration errors and scene deformation. To deal with cumulative errors, we present a global alignment algorithm that draws upon techniques commonly used in probabilistic robotics. To accommodate scene deformation, we present a local alignment algorithm that incorporates deformable surface models into the mosaicing framework. These algorithms are demonstrated on image sequences acquired in vivo with various imaging devices including a hand-held dual-axes confocal microscope, a miniature two-photon microscope, and a commercially available confocal microendoscope.
View details for DOI 10.1109/TBME.2010.2085082
View details for Web of Science ID 000285515500020
View details for PubMedID 20934939
- Configuration Tracking for Continuum Manipulators With Coupled Tendon Drive IEEE TRANSACTIONS ON ROBOTICS 2009; 25 (4): 798-808
Task-Space Control of Continuum Manipulators with Coupled Tendon Drive
11th International Symposium on Experimental Robotics (ISER)
SPRINGER-VERLAG BERLIN. 2009: 271–280
View details for Web of Science ID 000268803300026
- Configuration Tracking for Continuum Manipulators with Coupled Tendon Drive. IEEE Transactions on Robotics 2009; 25 (4): 798-808
- Mechanics Modeling of Tendon-Driven Continuum Manipulators IEEE TRANSACTIONS ON ROBOTICS 2008; 24 (6): 1262-1273
Vision based 3-D shape sensing of flexible manipulators
IEEE International Conference on Robotics and Automation
IEEE. 2008: 2940–2947
View details for Web of Science ID 000258095002034
- Real-Time Image Mosaicing with a Hand-Held Dual-Axis Confocal Microscope. 2008
- Vision Based 3-D Shape Sensing of Flexible Manipulators. 2008
- Task-space Feedback Control of Continuum Manipulators with Coupled Tendon Drive. 2008
- Mechanics Modeling of Tendon Driven Continuum Manipulators. IEEE Transactions on Robotics. 2008; 24 (6): 1262-1273
- Real-time image mosaicing with a hand-held dual-axes confocal microscope Conference on Endoscopic Microscopy III SPIE-INT SOC OPTICAL ENGINEERING. 2008
Real-Time Image Mosaicing for Medical Applications
15th Conference on Medicine Meets Virtual Reality
I O S PRESS. 2007: 304–309
In this paper we describe the development of a robotically-assisted image mosaicing system for medical applications. The processing occurs in real-time due to a fast initial image alignment provided by robotic position sensing. Near-field imaging, defined by relatively large camera motion, requires translations as well as pan and tilt orientations to be measured. To capture these measurements we use 5-d.o.f. sensing along with a hand-eye calibration to account for sensor offset. This sensor-based approach speeds up the mosaicing, eliminates cumulative errors, and readily handles arbitrary camera motions. Our results have produced visually satisfactory mosaics on a dental model but can be extended to other medical images.
View details for Web of Science ID 000270613800069
View details for PubMedID 17377290
- Deformable Image Mosaicing for Optical Biopsy. 2007
Deformable image mosaicing for optical biopsy
11th IEEE International Conference on Computer Vision
IEEE. 2007: 2212–2219
View details for Web of Science ID 000255099302025
Robotic technology in surgery: past, present, and future
AMERICAN JOURNAL OF SURGERY
2004; 188 (4A): 2S-15S
It has been nearly 20 years since the first appearance of robotics in the operating room. In that time, much progress has been made in integrating robotic technologies with surgical instrumentation, as evidenced by the many thousands of successful robot-assisted cases. However, to build on past success and to fully leverage the potential of surgical robotics in the future, it is essential to maximize a shared understanding and communication among surgeons, engineers, entrepreneurs, and healthcare administrators. This article provides an introduction to medical robotic technologies, develops a possible taxonomy, reviews the evolution of a surgical robot, and discusses future prospects for innovation. Robotic surgery has demonstrated some clear benefits. It remains to be seen where these benefits will outweigh the associated costs over the long term. In the future, surgical robots should be smaller, less expensive, easier to operate, and should seamlessly integrate emerging technologies from a number of different fields. Such advances will enable continued progress in surgical instrumentation and, ultimately, surgical care.
View details for DOI 10.1016/j.amjsung.2004.08.025
View details for Web of Science ID 000224479800003
View details for PubMedID 15476646