Digital assessment of speech in Huntington disease

Background

Speech changes are an early symptom of Huntington disease (HD) and may occur prior to other motor and cognitive symptoms. Assessment of HD commonly uses clinician-rated outcome measures, which can be limited by observer variability and episodic administration. Speech symptoms are well suited for evaluation by digital measures which can enable sensitive, frequent, passive, and remote administration.

Methods

We collected audio recordings using an external microphone of 36 (18 HD, 7 prodromal HD, and 11 control) participants completing passage reading, counting forward, and counting backwards speech tasks. Motor and cognitive assessments were also administered. Features including pausing, pitch, and accuracy were automatically extracted from recordings using the BioDigit Speech software and compared between the three groups. Speech features were also analyzed by the Unified Huntington Disease Rating Scale (UHDRS) dysarthria score. Random forest machine learning models were implemented to predict clinical status and clinical scores from speech features.

Results

Significant differences in pausing, intelligibility, and accuracy features were observed between HD, prodromal HD, and control groups for the passage reading task (e.g., p < 0.001 with Cohen'd = -2 between HD and control groups for pause ratio). A few parameters were significantly different between the HD and control groups for the counting forward and backwards speech tasks. A random forest classifier predicted clinical status from speech tasks with a balanced accuracy of 73% and an AUC of 0.92. Random forest regressors predicted clinical outcomes from speech features with mean absolute error ranging from 2.43-9.64 for UHDRS total functional capacity, motor and dysarthria scores, and explained variance ranging from 14 to 65%. Montreal Cognitive Assessment scores were predicted with mean absolute error of 2.3 and explained variance of 30%.

Conclusion

Speech data have the potential to be a valuable digital measure of HD progression, and can also enable remote, frequent disease assessment in prodromal HD and HD. Clinical status and disease severity were predicted from extracted speech features using random forest machine learning models. Speech measurements could be leveraged as sensitive marker of clinical onset and disease progression in future clinical trials.

Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults

INTRODUCTION

Current cognitive assessments suffer from floor/ceiling and practice effects, poor psychometric performance in mild cases, and repeated assessment effects. This study explores the use of digital speech analysis as an alternative tool for determining cognitive impairment. The study specifically focuses on identifying the digital speech biomarkers associated with cognitive impairment and its severity.

METHODS

We recruited older adults with varying cognitive health. Their speech data, recorded via a wearable microphone during the reading aloud of a standard passage, were processed to derive digital biomarkers such as timing, pitch, and loudness. Cohen's d effect size highlighted group differences, and correlations were drawn to the Montreal Cognitive Assessment (MoCA). A stepwise approach using a Random Forest model was implemented to distinguish cognitive states using speech data and predict MoCA scores based on highly correlated features.

RESULTS

The study comprised 59 participants, with 36 demonstrating cognitive impairment and 23 serving as cognitively intact controls. Among all assessed parameters, similarity, as determined by Dynamic Time Warping (DTW), exhibited the most substantial positive correlation (rho = 0.529, p < 0.001), while timing parameters, specifically the ratio of extra words, revealed the strongest negative correlation (rho = -0.441, p < 0.001) with MoCA scores. Optimal discriminative performance was achieved with a combination of four speech parameters: total pause time, speech-to-pause ratio, similarity via DTW, and intelligibility via DTW. Precision and balanced accuracy scores were found to be 88.1 ± 1.2% and 76.3 ± 1.3%, respectively.

DISCUSSION

Our research proposes that reading-derived speech data facilitates the differentiation between cognitively impaired individuals and cognitively intact, age-matched older adults. Specifically, parameters based on timing and similarity within speech data provide an effective gauge of cognitive impairment severity. These results suggest speech analysis as a viable digital biomarker for early detection and monitoring of cognitive impairment, offering novel approaches in dementia care.

A deep learning wearable-based solution for continuous at-home monitoring of upper limb goal-directed movements

Introduction

Monitoring upper limb function is crucial for tracking progress, assessing treatment effectiveness, and identifying potential problems or complications. Hand goal-directed movements (GDMs) are a crucial aspect of daily life, reflecting planned motor commands with hand trajectories towards specific target locations. Previous studies have shown that GDM tasks can detect early changes in upper limb function in neurodegenerative diseases and can be used to track disease progression over time.

Methods

In this study, we used accelerometer data from stroke survivor participants and controls doing activities of daily living to develop an automated deep learning approach to detect GDMs. The model performance for detecting GDM or non-GDM from windowed data achieved an AUC of 0.9, accuracy 0.83, sensitivity 0.81, specificity 0.84 and F1 0.82.

Results

We further validated the utility of detecting GDM by extracting features from GDM periods and using these features to classify whether the measurements are collected from a stroke survivor or a control participant, and to predict the Fugl-Meyer assessment score from stroke survivors.

Discussion

This study presents a promising and reliable tool for monitoring upper limb function in a real-world setting, and assessing biomarkers related to upper limb health in neurological, neuromuscular and muscles disorders.

Remote at-home wearable-based gait assessments in Progressive Supranuclear Palsy compared to Parkinson's Disease

BACKGROUND

Wearable sensors can differentiate Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) in laboratory settings but have not been tested in remote settings.

OBJECTIVES

To compare gait and balance in PSP and PD remotely using wearable-based assessments.

METHODS

Participants with probable PSP or probable/clinically established PD with reliable caregivers, still able to ambulate 10 feet unassisted, were recruited, enrolled, and consented remotely and instructed by video conference to operate a study-specific tablet solution (BioDigit Home ™) and to wear three inertial sensors (LEGSys™, BioSensics LLC, Newton, MA USA) while performing the Timed Up and Go, 5 × sit-to-stand, and 2-min walk tests. PSPRS and MDS-UPDRS scores were collected virtually or during routine clinical visits.

RESULTS

Between November, 2021- November, 2022, 27 participants were screened of whom 3 were excluded because of technological difficulties. Eleven PSP and 12 PD participants enrolled, of whom 10 from each group had complete analyzable data. Demographics were well-matched (PSP mean age = 67.6 ± 1.3 years, 40% female; PD mean age = 70.3 ± 1.8 years, 40% female) while disease duration was significantly shorter in PSP (PSP 14 ± 3.5 months vs PD 87.9 ± 16.9 months). Gait parameters showed significant group differences with effect sizes ranging from d = 1.0 to 2.27. Gait speed was significantly slower in PSP: 0.45 ± 0.06 m/s vs. 0.79 ± 0.06 m/s in PD (d = 1.78, p < 0.001).

CONCLUSION

Our study demonstrates the feasibility of measuring gait in PSP and PD remotely using wearable sensors. The study provides insight into digital biomarkers for both neurodegenerative diseases.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04753320, first posted Febuary 15, 2021.

Using Deep Learning to Detect the Presence and Location of Hemoperitoneum on the Focused Assessment with Sonography in Trauma (FAST) Examination in Adults

Abdominal ultrasonography has become an integral component of the evaluation of trauma patients. Internal hemorrhage can be rapidly diagnosed by finding free fluid with point-of-care ultrasound (POCUS) and expedite decisions to perform lifesaving interventions. However, the widespread clinical application of ultrasound is limited by the expertise required for image interpretation. This study aimed to develop a deep learning algorithm to identify the presence and location of hemoperitoneum on POCUS to assist novice clinicians in accurate interpretation of the Focused Assessment with Sonography in Trauma (FAST) exam. We analyzed right upper quadrant (RUQ) FAST exams obtained from 94 adult patients (44 confirmed hemoperitoneum) using the YoloV3 object detection algorithm. Exams were partitioned via fivefold stratified sampling for training, validation, and hold-out testing. We assessed each exam image-by-image using YoloV3 and determined hemoperitoneum presence for the exam using the detection with highest confidence score. We determined the detection threshold as the score that maximizes the geometric mean of sensitivity and specificity over the validation set. The algorithm had 95% sensitivity, 94% specificity, 95% accuracy, and 97% AUC over the test set, significantly outperforming three recent methods. The algorithm also exhibited strength in localization, while the detected box sizes varied with a 56% IOU averaged over positive cases. Image processing demonstrated only 57-ms latency, which is adequate for real-time use at the bedside. These results suggest that a deep learning algorithm can rapidly and accurately identify the presence and location of free fluid in the RUQ of the FAST exam in adult patients with hemoperitoneum.

Utilizing speech analysis to differentiate progressive supranuclear palsy from Parkinson's disease

INTRODUCTION

Distinguishing Parkinson's disease (PD) from Progressive supranuclear palsy (PSP) at early disease stages is important for clinical trial enrollment and clinical care/prognostication.

METHODS

We recruited 21 participants with PSP(n = 11) or PD(n = 10) with reliable caregivers. Standardized passage reading, counting, and sustained phonation were recorded on the BioDigit Home tablet (BioSensics LLC, Newton, MA USA), and speech features from the assessments were analyzed using the BioDigit Speech platform (BioSensics LLC, Newton, MA USA). An independent t-test was performed to compare each speech feature between PSP and PD participants. We also performed Spearman's correlations to evaluate associations between speech measures and clinical scores (e.g., PSP rating scales and MoCA). In addition, the model's performance in classifying PSP and PD was evaluated using Rainbow passage reading analysis.

RESULTS

During Rainbow passage reading, PSP participants had a significantly slower articulation rate (2.45(0.49) vs 3.60(0.47) words/minute), lower speech-to-pause ratio (2.33(1.08) vs 3.67(1.18)), intelligibility dynamic time warping (DTW, 0.26(0.19) vs 0.53(0.26)), and similarity DTW (0.43(0.27) vs 0.67(0.13)) compared to PD participants. PSP participants also had longer pause times (17.24(5.47) vs 8.45(3.13) sec) and longer total signal times (52.44(6.67) vs (36.67(6.73) sec) when reading the passage. In terms of the phonation 'a', PSP participants showed a significant higher spectral entropy, spectral centroid, and spectral spread compared to PD participants and no differences were found for phonation 'e'. PD participants had more accurate reverse number counts than PSP participants (14.89(3.86) vs 7.36(4.67)). PSP Rating Scale (PSPRS) dysarthria (r = 0.79, p = 0.004) and bulbar item scores (r = 0.803, p = 0.005) were positively correlated with articulation rate in reverse number counts. Correct reverse number counts were positively correlated with total Montreal Cognitive Assessment scores (r = 0.703, p = 0.016). Machine learning models using passage reading-derived measures obtained an AUC of 0.93, and the sensitivity/specificity in correctly classifying PSP and PD participants were 0.95 and 0.90, respectively.

CONCLUSION

Our study demonstrates the feasibility of differentiating PSP from PD using a digital health technology platform. Further multi-center studies are needed to expand and validate our initial findings.

Functional imaging through scattering medium via fluorescence speckle demixing and localization

Recently, fluorescence-based optical techniques have emerged as a powerful tool to probe information in the mammalian brain. However, tissue heterogeneities prevent clear imaging of deep neuron bodies due to light scattering. While several up-to-date approaches based on ballistic light allow to retrieve information at shallow depths inside the brain, non-invasive localization and functional imaging at depth still remains a challenge. It was recently shown that functional signals from time-varying fluorescent emitters located behind scattering samples could be retrieved by using a matrix factorization algorithm. Here we show that the seemingly information-less, low-contrast fluorescent speckle patterns recovered by the algorithm can be used to locate each individual emitter, even in the presence of background fluorescence. We test our approach by imaging the temporal activity of large groups of fluorescent sources behind different scattering phantoms mimicking biological tissues, and through a brain slice with a thickness of ∼200 µm.

Automated Bone Tumor Segmentation and Classification as Benign or Malignant Using Computed Tomographic Imaging

The purpose of this study was to pair computed tomography (CT) imaging and machine learning for automated bone tumor segmentation and classification to aid clinicians in determining the need for biopsy. In this retrospective study (March 2005-October 2020), a dataset of 84 femur CT scans (50 females and 34 males, 20 years and older) with definitive histologic confirmation of bone lesion (71% malignant) were leveraged to perform automated tumor segmentation and classification. Our method involves a deep learning architecture that receives a DICOM slice and predicts (i) a segmentation mask over the estimated tumor region, and (ii) a corresponding class as benign or malignant. Class prediction for each case is then determined via majority voting. Statistical analysis was conducted via fivefold cross validation, with results reported as averages along with 95% confidence intervals. Despite the imbalance between benign and malignant cases in our dataset, our approach attains similar classification performances in specificity (75%) and sensitivity (79%). Average segmentation performance attains 56% Dice score and reaches up to 80% for an image slice in each scan. The proposed approach establishes the first steps in developing an automated deep learning method on bone tumor segmentation and classification from CT imaging. Our approach attains comparable quantitative performance to existing deep learning models using other imaging modalities, including X-ray. Moreover, visual analysis of bone tumor segmentation indicates that our model is capable of learning typical tumor characteristics and provides a promising direction in aiding the clinical decision process for biopsy.

Automated detection and localization of pericardial effusion from point-of-care cardiac ultrasound examination

Focused Assessment with Sonography in Trauma (FAST) exam is the standard of care for pericardial and abdominal free fluid detection in emergency medicine. Despite its life saving potential, FAST is underutilized due to requiring clinicians with appropriate training and practice. To aid ultrasound interpretation, the role of artificial intelligence has been studied, while leaving room for improvement in localization information and computation time. The purpose of this study was to develop and test a deep learning approach to rapidly and accurately identify both the presence and location of pericardial effusion on point-of-care ultrasound (POCUS) exams. Each cardiac POCUS exam is analyzed image-by-image via the state-of-the-art YoloV3 algorithm and pericardial effusion presence is determined from the most confident detection. We evaluate our approach over a dataset of POCUS exams (cardiac component of FAST and ultrasound), comprising 37 cases with pericardial effusion and 39 negative controls. Our algorithm attains 92% specificity and 89% sensitivity in pericardial effusion identification, outperforming existing deep learning approaches, and localizes pericardial effusion by 51% Intersection Over Union with ground-truth annotations. Moreover, image processing demonstrates only 57 ms latency. Experimental results demonstrate the feasibility of rapid and accurate pericardial effusion detection from POCUS exams for physician overread.

Functional imaging through scattering medium via fluorescence speckle demixing and localization

Recently, fluorescence-based optical techniques have emerged as a powerful tool to probe information in the mammalian brain. However, tissue heterogeneities prevent clear imaging of deep neuron bodies due to light scattering. While several up-to-date approaches based on ballistic light allow to retrieve information at shallow depths inside the brain, non-invasive localization and functional imaging at depth still remains a challenge. It was recently shown that functional signals from time-varying fluorescent emitters located behind scattering samples could be retrieved by using a matrix factorization algorithm. Here we show that the seemingly information-less, low-contrast fluorescent speckle patterns recovered by the algorithm can be used to locate each individual emitter, even in the presence of background fluorescence. We test our approach by imaging the temporal activity of large groups of fluorescent sources behind different scattering phantoms mimicking biological tissues, and through a brain slice with a thickness of ~200 micron.

Dual-Task Upper Extremity Motor Performance Measured by Video Processing as Cognitive-Motor Markers for Older Adults

INTRODUCTION

The use of dual-task model such as dual-task gait has been extensively studied to assess cognitive-motor performance among older adults. However, space restriction and safety factor limit its applications in remote assessment. To address the gap, we propose a video processing-based approach to remotely quantify cognitive-motor performance using a 20-s repetitive elbow flexion-extension test with dual-task condition, called video-based motoric-cognitive meter (MCM).

METHODS

Eighteen older participants (age: 78.6 ± 6.5 years) who were clinically diagnosed as having either mild cognitive impairment or dementia were included in this study. Participants were asked to perform 20-s repetitive elbow flexion-extension exercise with a memory exercise by counting backward from a two-digit number. During the test, all movements of the forearm were recorded by a video camera. As a comparator, a validated wrist-worn sensor was used, which allowed quantifying upper extremity kinematics.

RESULTS

The results showed a good agreement (r ≥ 0.530 and ICC2,1 ≥ 0.681) between the derived dual-task upper extremity motor performance from the proposed video-based MCM and a clinically validated sensor-based MCM. We also observed moderate correlations (r ≥ 0.496) between some measures of video-based MCM (flexion time, extension time, and flexion-extension time) and clinical cognitive scale (Mini-Mental State Examination [MMSE]). Additionally, some measures of dual-task upper extremity motor performance (speed, flexion time, extension time, and flexion-extension time) were associated with dual-task gait speed (r ≥ 0.557), which has been found to be correlated with cognitive impairment. Lastly, the selected dual-task motor performance metric (flexion time) was sensitive to predict MMSE scores in linear regression analyses with statistical significance (adjusted R2 = 0.306, p = 0.025).

CONCLUSION

This study proposes a video processing-based approach to analyze dual-task upper extremity motor performance from a simple and convenient upper extremity function test. The results indicate concurrent validity of the proposed video-based MCM compared with the sensor-based MCM, and associations between dual-task upper extremity motor performance and clinically validated cognitive markers (MMSE scores and dual-task gait). Future studies are warranted to explore sensitivity of this solution to promote remote assessment of cognitive-motor performance among older adults in telehealth applications.

Tele-Medicine Based and Self-Administered Interactive Exercise Program (Tele-Exergame) to Improve Cognition in Older Adults with Mild Cognitive Impairment or Dementia: A Feasibility, Acceptability, and Proof-of-Concept Study

Improved life expectancy is increasing the number of older adults who suffer from motor-cognitive decline. Unfortunately, conventional balance exercise programs are not tailored to patients with cognitive impairments, and exercise adherence is often poor due to unsupervised settings. This study describes the acceptability and feasibility of a sensor-based in-home interactive exercise system, called tele-Exergame, used by older adults with mild cognitive impairment (MCI) or dementia. Our tele-Exergame is specifically designed to improve balance and cognition during distractive conditioning while a telemedicine interface remotely supervises the exercise, and its exercises are gamified balance tasks with explicit augmented visual feedback. Fourteen adults with MCI or dementia (Age = 68.1 ± 5.4 years, 12 females) participated and completed exergame twice weekly for six weeks at their homes. Before and after 6 weeks, participants' acceptance was assessed by Technology Acceptance Model (TAM) questionnaire, and participants' cognition and anxiety level were evaluated by the Montreal Cognitive Assessment (MoCA) and Beck Anxiety Inventory (BAI), respectively. Results support acceptability, perceived benefits, and positive attitudes toward the use of the system. The findings of this study support the feasibility, acceptability, and potential benefit of tele-Exergame to preserve cognitive function among older adults with MCI and dementia.

Digital Biomarkers of Gait and Balance in Diabetic Foot, Measurable by Wearable Inertial Measurement Units: A Mini Review

People with diabetic foot frequently exhibit gait and balance dysfunction. Recent advances in wearable inertial measurement units (IMUs) enable to assess some of the gait and balance dysfunction associated with diabetic foot (i.e., digital biomarkers of gait and balance). However, there is no review to inform digital biomarkers of gait and balance dysfunction related to diabetic foot, measurable by wearable IMUs (e.g., what gait and balance parameters can wearable IMUs collect? Are the measurements repeatable?). Accordingly, we conducted a web-based, mini review using PubMed. Our search was limited to human subjects and English-written papers published in peer-reviewed journals. We identified 20 papers in this mini review. We found preliminary evidence of digital biomarkers of gait and balance dysfunction in people with diabetic foot, such as slow gait speed, large gait variability, unstable gait initiation, and large body sway. However, due to heterogeneities in included papers in terms of study design, movement tasks, and small sample size, more studies are recommended to confirm this preliminary evidence. Additionally, based on our mini review, we recommend establishing appropriate strategies to successfully incorporate wearable-based assessment into clinical practice for diabetic foot care.

Objective Assessment of Upper-Extremity Motor Functions in Spinocerebellar Ataxia Using Wearable Sensors

The study presents a novel approach to objectively assessing the upper-extremity motor symptoms in spinocerebellar ataxia (SCA) using data collected via a wearable sensor worn on the patient's wrist during upper-extremity tasks associated with the Assessment and Rating of Ataxia (SARA). First, we developed an algorithm for detecting/extracting the cycles of the finger-to-nose test (FNT). We extracted multiple features from the detected cycles and identified features and parameters correlated with the SARA scores. Additionally, we developed models to predict the severity of symptoms based on the FNT. The proposed technique was validated on a dataset comprising the seventeen (n = 17) participants' assessments. The cycle detection technique showed an accuracy of 97.6% in a Bland-Altman analysis and a 94% accuracy (F1-score of 0.93) in predicting the severity of the FNT. Furthermore, the dependency of the upper-extremity tests was investigated through statistical analysis, and the results confirm dependency and potential redundancies in the upper-extremity SARA assessments. Our findings pave the way to enhance the utility of objective measures of SCA assessments. The proposed wearable-based platform has the potential to eliminate subjectivity and inter-rater variabilities in assessing ataxia.

Smart-Home Concept for Remote Monitoring of Instrumental Activities of Daily Living (IADL) in Older Adults with Cognitive Impairment: A Proof of Concept and Feasibility Study

Assessment of instrumental activities of daily living (IADL) is essential for the diagnosis and staging of dementia. However, current IADL assessments are subjective and cannot be administered remotely. We proposed a smart-home design, called IADLSys, for remote monitoring of IADL. IADLSys consists of three major components: (1) wireless physical tags (pTAG) attached to objects of interest, (2) a pendant-sensor to monitor physical activities and detect interaction with pTAGs, and (3) an interactive tablet as a gateway to transfer data to a secured cloud. Four studies, including an exploratory clinical study with five older adults with clinically confirmed cognitive impairment, who used IADLSys for 24 h/7 days, were performed to confirm IADLSys feasibility, acceptability, adherence, and validity of detecting IADLs of interest and physical activity. Exploratory tests in two cases with severe and mild cognitive impairment, respectively, revealed that a case with severe cognitive impairment either overestimated or underestimated the frequency of performed IADLs, whereas self-reporting and objective IADL were comparable for the case with mild cognitive impairment. This feasibility and acceptability study may pave the way to implement the smart-home concept to remotely monitor IADL, which in turn may assist in providing personalized support to people with cognitive impairment, while tracking the decline in both physical and cognitive function.

Assessment of gait and balance impairment in people with spinocerebellar ataxia using wearable sensors

OBJECTIVE

To explore the use of wearable sensors for objective measurement of motor impairment in spinocerebellar ataxia (SCA) patients during clinical assessments of gait and balance.

METHODS

In total, 14 patients with genetically confirmed SCA (mean age 61.6 ± 8.6 years) and 4 healthy controls (mean age 49.0 ± 16.4 years) were recruited through the Massachusetts General Hospital (MGH) Ataxia Center. Participants donned seven inertial sensors while performing two independent trials of gait and balance assessments from the Scale for the Assessment and Rating of Ataxia (SARA) and Brief Ataxia Rating Scale (BARS2). Univariate analysis was used to identify sensor-derived metrics from wearable sensors that discriminate motor function between the SCA and control groups. Multivariate linear regression models were used to estimate the subjective in-person SARA/BARS2 ratings. Spearman correlation coefficients were used to evaluate the performance of the model.

RESULTS

Stride length variability, stride duration, cadence, stance phase, pelvis sway, and turn duration were different between SCA and controls (p < 0.05). Similarly, sway and sway velocity of the ankle, hip, and center of mass differentiated SCA and controls (p < 0.05). Using these features, linear regression models showed moderate-to-strong correlation with clinical scores from the in-person rater during SARA assessments of gait (r = 0.73, p = 0.003) and stance (r = 0.90, p < 0.001) and the BARS2 gait assessment (r = 0.74, p = 0.003).

CONCLUSION

This study demonstrates that sensor-derived metrics can potentially be used to estimate the level of motor impairment in patient with SCA quickly and objectively. Thus, digital biomarkers from wearable sensors have the potential to be an integral tool for SCA clinical trials and care.

Mobility Performance in Community-Dwelling Older Adults: Potential Digital Biomarkers of Concern about Falling

INTRODUCTION

Concern about falling is a prevalent worry among community-dwelling older adults and may contribute to a decline in physical and mental health. This study aimed to examine the association between mobility performance and concern about falling.

METHODS

Older adults aged 65 years and older, with Mini-Mental State Examination score ≥24, and ambulatory (with or without the assistive device) were included. Concern about falling was evaluated with Falls Efficacy Scale-International (FES-I) scores. Participants with high concern about falling were identified using the cutoff of FES-I ≥23. Participants' motor capacity was assessed in standardized walking tests under single- and dual-task conditions. Participants' mobility performance was measured based on a 48-h trunk accelerometry signal from a wearable pendant sensor.

RESULTS

No significant differences were observed at participant characteristics across groups with different levels of concern about falling (low: N = 64, age = 76.3 ± 7.2 years, female = 46%; high: N = 59, age = 79.3 ± 9.1 years, female = 47%), after propensity matching with BMI, age, depression, and cognition. With adjustment of motor capacity (stride velocity and stride length under single- and dual-task walking conditions), participants with high concern about falling had significantly poorer mobility performance than those with low concern about falling, including lower walking quantity (walking bouts, steps and time per day, and walking bout average, walking bout variability, and longest walking bout, p ≤ 0.013), and poorer daily-life gait (stride velocity and gait variability, p ≤ 0.023), and poorer walking quality (frontal gait symmetry, and trunk acceleration and velocity intensity, p ≤ 0.041). The selected mobility performance metrics (daily steps and frontal gait symmetry) could significantly contribute to identifying older adults with high concern about falling (p ≤ 0.042), having better model performance (p = 0.036) than only walking quantity (daily steps) with adjustment of confounding effects from the motor capacity (stride length under dual-task walking condition).

CONCLUSION

There is an association between mobility performance and concern about falling in older adults. Mobility performance metrics can serve as predictors to identify older adults with high concern about falling, potentially providing digital biomarkers for clinicians to remotely track older adults' change of concern about falling via applications of remote patient monitoring.

Bending behavior of biomimetic scale covered beam with tunable stiffness scales

Biomimetic scales provide a convenient template to tailor the bending stiffness of the underlying slender substrate due to their mutual sliding after engagement. Scale stiffness can therefore directly impact the substrate behavior, opening a potential avenue for substrate stiffness tunability. Here, we have developed a biomimetic beam, which is covered by tunable stiffness scales. Scale tunability is achieved by specially designed plate like scales consisting of layers of low melting point alloy (LMPA) phase change materials fully enclosed inside a soft polymer. These composite scales can transition between stiff and soft states by straddling the temperatures across LMPA melting points thereby drastically altering stiffness. We experimentally analyze the bending behavior of biomimetic beams covered with tunable stiffness scales of two architectures—one with single enclosure of LMPA and one with two enclosures of different melting point LMPAs. These architectures provide a continuous stiffness change of the underlying substrate post engagement, controlled by the operating temperature. We characterize this response using three-point bending experiments at various temperature profiles. Our results demonstrate for the first time, the pronounced and reversible tunability in the bending behavior of biomimetic scale covered beam, which are strongly dependent on the scale material and architecture. Particularly, it is shown that the bending stiffness of the biomimetic scale covered beam can be actively and reversibly tuned by a factor of up to 7. The developed biomimetic beam has applications in soft robotic grippers, smart segmented armors, deployable structures and soft swimming robots.

Computational modeling of human bone fracture healing affected by different conditions of initial healing stage

Background

Bone healing process includes four phases: inflammatory response, soft callus formation, hard callus development, and remodeling. Mechanobiological models have been used to investigate the role of various mechanical and biological factors on bone healing. However, the effects of initial healing phase, which includes the inflammatory stage, the granulation tissue formation, and the initial callus formation during the first few days post-fracture, are generally neglected in such studies.

Methods

In this study, we developed a finite-element-based model to simulate different levels of diffusion coefficient for mesenchymal stem cell (MSC) migration, Young’s modulus of granulation tissue, callus thickness and interfragmentary gap size to understand the modulatory effects of these initial phase parameters on bone healing.

Results

The results quantified how faster MSC migration, stiffer granulation tissue, thicker callus, and smaller interfragmentary gap enhanced healing to some extent. However, after a certain threshold, a state of saturation was reached for MSC migration rate, granulation tissue stiffness, and callus thickness. Therefore, a parametric study was performed to verify that the callus formed at the initial phase, in agreement with experimental observations, has an ideal range of geometry and material properties to have the most efficient healing time.

Conclusions

Findings from this paper quantified the effects of the initial healing phase on healing outcome to better understand the biological and mechanobiological mechanisms and their utilization in the design and optimization of treatment strategies. It is also demonstrated through a simulation that for fractures, where bone segments are in close proximity, callus development is not required. This finding is consistent with the concepts of primary and secondary bone healing.

Origami-based Building Blocks for Modular Construction of Foldable Structures

Origami, widely known as the ancient Japanese art of paper folding, has recently inspired a new paradigm of design for mechanical metamaterials and deployable structural systems. However, lack of rationalized design guidelines and scalable manufacturing methods has hindered their applications. To address this limitation, we present analytical methods for designing origami-based closed-loop units with inherent foldability, and for predicting their folding response (e.g., folding force, bistability, and area and volume change by folding). These units can be employed as building blocks for application-driven design and modular construction of foldable structures with desired performance and manufacturing scalability.

Bone fracture healing in mechanobiological modeling: A review of principles and methods

Bone fracture is a very common body injury. The healing process is physiologically complex, involving both biological and mechanical aspects. Following a fracture, cell migration, cell/tissue differentiation, tissue synthesis, and cytokine and growth factor release occur, regulated by the mechanical environment. Over the past decade, bone healing simulation and modeling has been employed to understand its details and mechanisms, to investigate specific clinical questions, and to design healing strategies. The goal of this effort is to review the history and the most recent work in bone healing simulations with an emphasis on both biological and mechanical properties. Therefore, we provide a brief review of the biology of bone fracture repair, followed by an outline of the key growth factors and mechanical factors influencing it. We then compare different methodologies of bone healing simulation, including conceptual modeling (qualitative modeling of bone healing to understand the general mechanisms), biological modeling (considering only the biological factors and processes), and mechanobiological modeling (considering both biological aspects and mechanical environment). Finally we evaluate different components and clinical applications of bone healing simulation such as mechanical stimuli, phases of bone healing, and angiogenesis.

Origami-based cellular metamaterial with auxetic, bistable, and self-locking properties

We present a novel cellular metamaterial constructed from Origami building blocks based on Miura-ori fold. The proposed cellular metamaterial exhibits unusual properties some of which stemming from the inherent properties of its Origami building blocks, and others manifesting due to its unique geometrical construction and architecture. These properties include foldability with two fully-folded configurations, auxeticity (i.e., negative Poisson’s ratio), bistability, and self-locking of Origami building blocks to construct load-bearing cellular metamaterials. The kinematics and force response of the cellular metamaterial during folding were studied to investigate the underlying mechanisms resulting in its unique properties using analytical modeling and experiments.

Highly Anisotropic Adhesive Film Made from Upside-Down, Flat, and Uniform Vertically Aligned CNTs

We have created a multifunctional dry adhesive film with transferred vertically aligned carbon nanotubes (VA-CNTs). This unique VA-CNT film was fabricated by a multistep transfer process, converting the flat and uniform bottom of VA-CNTs grown on atomically flat silicon wafer substrates into the top surface of an adhesive layer. Unlike as-grown VA-CNTs, which have a nonuniform surface, randomly entangled CNT arrays, and a weak interface between the CNTs and substrates, this transferred VA-CNT film shows an extremely high coefficient of static friction (COF) of up to 60 and a shear adhesion force 30 times higher (12 N/cm²) than that of the as-grown VA-CNTs under a very small preloading of 0.2 N/cm². Moreover, a near-zero normal adhesion force was observed with 20 mN/cm² preloading and a maximum 100-μm displacement in a piezo scanner, demonstrating ideal properties for an artificial gecko foot. Using this unique structural feature and anisotropic adhesion properties, we also demonstrate effective removal and assembly of nanoparticles into organized micrometer-scale circular and line patterns by a single brushing of this flat and uniform VA-CNT film.

Influence of disruption of the acromioclavicular and coracoclavicular ligaments on glenohumeral motion: a kinematic evaluation

Background

Changes to the integrity of the acromioclavicular (AC) joint impact scapulothoracic and clavicular kinematics. AC ligaments provide anterior-posterior stability, while the coracoclavicular (CC) ligaments provide superior-inferior stability and a restraint to scapular internal rotation. The purpose of this cadaveric study was to describe the effect of sequential AC and CC sectioning on glenohumeral (GH) kinematics during abduction (ABD) of the arm. We hypothesized that complete AC ligament insult would result in altered GH translation in the anterior-posterior plane during abduction, while subsequent sectioning of both CC ligaments would result in an increasing inferior shift in GH translation.

Methods

Six cadaveric shoulders were studied to evaluate the impact of sequential sectioning of AC and CC ligaments on GH kinematics throughout an abduction motion in the coronal plane. Following an examination of the baseline, uninjured kinematics, the AC ligaments were then sectioned sequentially: (1) Anterior, (2) Inferior, (3) Posterior, and (4) Superior. Continued sectioning of CC ligamentous structures followed: the (5) trapezoid and then the (6) conoid ligaments. For each group, the GH translation and the area under the curve (AUC) were measured during abduction using an intact cadaveric shoulder. Total translation was calculated for each condition between ABD 30° and ABD 150° using the distance formula, and a univariate analysis was used to compare total translation for each axis during the different conditions.

Results

GH kinematics were not altered following sequential resection of the AC ligaments. Disruption of the trapezoid resulted in significant anterior and lateral displacement of the center of GH rotation. Sectioning the conoid ligament further increased the inferior shift in GH displacement.

Conclusion

A combined injury of the AC and CC ligaments significantly alters GH kinematics during abduction. Type III AC separations, result in a significant change in the shoulder’s motion and may warrant surgical reconstruction to restore normal function.

Curved Beam Computed Tomography based Structural Rigidity Analysis of Bones with Simulated Lytic Defect: A Comparative Study with Finite Element Analysis

In this paper, a CT based structural rigidity analysis (CTRA) method that incorporates bone intrinsic local curvature is introduced to assess the compressive failure load of human femur with simulated lytic defects. The proposed CTRA is based on a three dimensional curved beam theory to obtain critical stresses within the human femur model. To test the proposed method, ten human cadaveric femurs with and without simulated defects were mechanically tested under axial compression to failure. Quantitative computed tomography images were acquired from the samples, and CTRA and finite element analysis were performed to obtain the failure load as well as rigidities in both straight and curved cross sections. Experimental results were compared to the results obtained from FEA and CTRA. The failure loads predicated by curved beam CTRA and FEA are in agreement with experimental results. The results also show that the proposed method is an efficient and reliable method to find both the location and magnitude of failure load. Moreover, the results show that the proposed curved CTRA outperforms the regular straight beam CTRA, which ignores the bone intrinsic curvature and can be used as a useful tool in clinical practices.

Hierarchical analysis and multi-scale modelling of rat cortical and trabecular bone

The aim of this study was to explore the hierarchical arrangement of structural properties in cortical and trabecular bone and to determine a mathematical model that accurately predicts the tissue's mechanical properties as a function of these indices. By using a variety of analytical techniques, we were able to characterize the structural and compositional properties of cortical and trabecular bones, as well as to determine the suitable mathematical model to predict the tissue's mechanical properties using a continuum micromechanics approach. Our hierarchical analysis demonstrated that the differences between cortical and trabecular bone reside mainly at the micro- and ultrastructural levels. By gaining a better appreciation of the similarities and differences between the two bone types, we would be able to provide a better assessment and understanding of their individual roles, as well as their contribution to bone health overall.

The effect of the rotator interval on glenohumeral kinematics during abduction

Background

The rotator interval (RI) has been exploited as a potentially benign point of entry into the glenohumeral (GH) joint. Bounded by the supraspinatus, subscapularis and coracoid process of the scapula, the RI is believed to be important in the shoulder’s soft tissue balancing and function. However, the role of the RI in shoulder kinematics is not fully understood. The purpose of this study is to describe the effect of the RI on GH motion during abduction of the arm.

Methods

Six shoulders from three cadaveric torsos were studied to assess the impact of changes in the RI during abduction under four conditions: Intact (Baseline), Opened, Repaired (repaired with side-to-side tissue approximation, no overlap) and Tightened (repaired with 1 cm overlap). For each group, the GH translation and area under the Curve (AUC) were measured during abduction using an intact cadaveric shoulder (intact torso).

Results

GH kinematics varied in response to each intervention and throughout the entire abduction arc. Opening the RI caused a significant change in GH translation. The Repair and Tightened groups behaved similarly along all axes of GH motion.

Conclusions

The RI is central to normal GH kinematics. Any insult to the tissue’s integrity alters the shoulder’s motion throughout abduction. In this model, closing the RI side-to-side has the same effect as tightening the RI. Since suture closure may offer the same benefit as tightening the RI, clinicians should consider this effect when treating patients with shoulder laxity. This investigation provides an improved perspective on the role of the RI on GH kinematics during abduction. When managing shoulder pathology, surgeons should consider how these different methods of RI closure affect the joint’s motion. In different circumstances, the surgical approach to the RI can be tailored to address each patient’s specific needs.

Hierarchical honeycomb auxetic metamaterials

Most conventional materials expand in transverse directions when they are compressed uniaxially resulting in the familiar positive Poisson’s ratio. Here we develop a new class of two dimensional (2D) metamaterials with negative Poisson’s ratio that contract in transverse directions under uniaxial compressive loads leading to auxeticity. This is achieved through mechanical instabilities (i.e., buckling) introduced by structural hierarchy and retained over a wide range of applied compression. This unusual behavior is demonstrated experimentally and analyzed computationally. The work provides new insights into the role of structural organization and hierarchy in designing 2D auxetic metamaterials, and new opportunities for developing energy absorbing materials, tunable membrane filters, and acoustic dampeners.

Posterior Capsular Plication Constrains the Glenohumeral Joint by Drawing the Humeral Head Closer to the Glenoid and Resisting Abduction

BACKGROUND

Shoulder pain is a common problem, with 30% to 50% of the American population affected annually. While the majority of these shoulder problems improve, there is a high rate of recurrence, as 54% of patients experience persistent symptoms 3 years after onset.

PURPOSE

Posterior shoulder tightness has been shown to alter glenohumeral (GH) kinematics. Clinically, posterior shoulder contractures result in a significant loss of internal rotation and abduction (ABD). In this study, the effect of a posterior capsular contracture on GH kinematics was investigated using an intact cadaveric shoulder without violating the joint capsule or the rotator cuff.

STUDY DESIGN

Controlled laboratory study.

METHODS

Glenohumeral motion, humeral load, and subacromial contact pressure were measured in 6 fresh-frozen left shoulders during passive ABD from 60° to 100° using an automated robotic upper extremity testing system. Baseline values were compared with the experimental condition in which the full thickness of posterior tissues was plicated without decompressing the joint capsule.

RESULTS

Posterior soft tissue plication resulted in increased compression between the humeral head and the glenoid (axial load) at 90° of ABD. Throughout ABD, the posterior contracture increased the anterior and superior moment on the humeral head, but it did not change the GH kinematics in this intact model. As a result, there was no increase in the subacromial contact pressure during ABD with posterior plication.

CONCLUSION

In an intact cadaveric shoulder, posterior contracture does not alter GH motion or subacromial contact pressure during passive ABD. By tightening the soft tissue envelope posteriorly, there is an increase in compressive load on the articular cartilage and anterior/superior force on the humeral head. These findings suggest that subacromial impingement in the setting of a posterior soft tissue contracture may result from alterations in scapulothoracic motion, not changes in GH kinematics.

CLINICAL RELEVANCE

This investigation demonstrates that posterior capsular plication increases the axial load on the shoulder joint during ABD. While a significant difference from baseline was observed in the plicated condition, posterior capsular plication did not change GH motion or subacromial contact pressure significantly.

Effects of Different Loading Patterns on the Trabecular Bone Morphology of the Proximal Femur Using Adaptive Bone Remodeling

In this study, the changes in the bone density of human femur model as a result of different loadings were investigated. The model initially consisted of a solid shell representing cortical bone encompassing a cubical network of interconnected rods representing trabecular bone. A computationally efficient program was developed that iteratively changed the structure of trabecular bone by keeping the local stress in the structure within a defined stress range. The stress was controlled by either enhancing existing beam elements or removing beams from the initial trabecular frame structure. Analyses were performed for two cases of homogenous isotropic and transversely isotropic beams. Trabecular bone structure was obtained for three load cases: walking, stair climbing and stumbling without falling. The results indicate that trabecular bone tissue material properties do not have a significant effect on the converged structure of trabecular bone. In addition, as the magnitude of the loads increase, the internal structure becomes denser in critical zones. Loading associated with the stumbling results in the highest density; whereas walking, considered as a routine daily activity, results in the least internal density in different regions. Furthermore, bone volume fraction at the critical regions of the converged structure is in good agreement with previously measured data obtained from combinations of dual X-ray absorptiometry (DXA) and computed tomography (CT). The results indicate that the converged bone architecture consisting of rods and plates are consistent with the natural bone morphology of the femur. The proposed model shows a promising means to understand the effects of different individual loading patterns on the bone density.

Biomechanics and mechanobiology of trabecular bone: a review

Trabecular bone is a highly porous, heterogeneous, and anisotropic material which can be found at the epiphyses of long bones and in the vertebral bodies. Studying the mechanical properties of trabecular bone is important, since trabecular bone is the main load bearing bone in vertebral bodies and also transfers the load from joints to the compact bone of the cortex of long bones. This review article highlights the high dependency of the mechanical properties of trabecular bone on species, age, anatomic site, loading direction, and size of the sample under consideration. In recent years, high resolution micro finite element methods have been extensively used to specifically address the mechanical properties of the trabecular bone and provide unique tools to interpret and model the mechanical testing experiments. The aims of the current work are to first review the mechanobiology of trabecular bone and then present classical and new approaches for modeling and analyzing the trabecular bone microstructure and macrostructure and corresponding mechanical properties such as elastic properties and strength.

Type-IV Pilus deformation can explain retraction behavior

Polymeric filament like type IV Pilus (TFP) can transfer forces in excess of 100 pN during their retraction before stalling, powering surface translocation(twitching). Single TFP level experiments have shown remarkable nonlinearity in the retraction behavior influenced by the external load as well as levels of PilT molecular motor protein. This includes reversal of motion near stall forces when the concentration of the PilT protein is loweblack significantly. In order to explain this behavior, we analyze the coupling of TFP elasticity and interfacial behavior with PilT kinetics. We model retraction as reaction controlled and elongation as transport controlled process. The reaction rates vary with TFP deformation which is modeled as a compound elastic body consisting of multiple helical strands under axial load. Elongation is controlled by monomer transport which suffer entrapment due to excess PilT in the cell periplasm. Our analysis shows excellent agreement with a host of experimental observations and we present a possible biophysical relevance of model parameters through a mechano-chemical stall force map.

Optimal fractal-like hierarchical honeycombs

Hexagonal honeycomb structures are known for their high strength and low weight. We construct a new class of fractal-appearing cellular metamaterials by replacing each three-edge vertex of a base hexagonal network with a smaller hexagon and iterating this process. The mechanical properties of the structure after different orders of the iteration are optimized. We find that the optimal structure (with highest in-plane stiffness for a given weight ratio) is self-similar but requires higher order hierarchy as the density vanishes. These results offer insights into how incorporating hierarchy in the material structure can create low-density metamaterials with desired properties and function.

Buckling of regular, chiral and hierarchical honeycombs under a general macroscopic stress state

An approach to obtain analytical closed-form expressions for the macroscopic ‘buckling strength’ of various two-dimensional cellular structures is presented. The method is based on classical beam-column end-moment behaviour expressed in a matrix form. It is applied to sample honeycombs with square, triangular and hexagonal unit cells to determine their buckling strength under a general macroscopic in-plane stress state. The results were verified using finite-element Eigenvalue analysis.

Anisotropic blistering instability of highly ellipsoidal shells

The formation of localized periodic structures in the deformation of elastic shells is well documented and is a familiar first stage in the crushing of a spherical shell such as a ping-pong ball. While spherical shells manifest such periodic structures as polygons, we present a new instability that is observed in the indentation of a highly ellipsoidal shell by a horizontal plate. Above a critical indentation depth, the plate loses contact with the shell in a series of well-defined "blisters" along the long axis of the ellipsoid. We characterize the onset of this instability and explain it using scaling arguments, numerical simulations, and experiments. We also characterize the properties of the blistering pattern by showing how the number of blisters and their size depend on both the geometrical properties of the shell and the indentation but not on the shell's elastic modulus. This blistering instability may be used to determine the thickness of highly ellipsoidal shells simply by squashing them between two plates.

Finite element analysis and computed tomography based structural rigidity analysis of rat tibia with simulated lytic defects

Finite element analysis (FEA), CT based structural rigidity analysis (CTRA) and mechanical testing is performed to assess the compressive failure load of rat tibia with simulated lytic defects. Twenty rat tibia were randomly assigned to four equal groups (n=5). Three of the groups included a simulated defect at various locations: anterior bone surface (Group 1), posterior bone surface (Group 2) and through bone defect (Group 3). The fourth group was a control group with no defect (Group 4). Microcomputed tomography was used to assess bone structural rigidity properties and to provide 3D model data for generation of the finite element models for each specimen. Compressive failure load calculated using CT derived rigidity parameters (FCTRA) was well correlated to failure load recorded in mechanical testing (R(2)=0.96). The relationships between mechanical testing failure load and the axial rigidity (R(2)=0.61), bending rigidity (R(2)=0.71) and FEA calculated failure loads, considering bone as an elastic isotropic (R(2)=0.75) and elastic transversely isotropic (R(2)=0.90) are also well correlated. CTRA stress, calculated adjacent to the defect, were also shown to be well correlated with yield stresses calculated using the minimum density at the weakest cross section (R(2)=0.72). No statistically significant relationship between apparent density and mechanical testing failure load was found (P=0.37). In summary, the results of this study indicate that CTRA analysis of bone strength correlates well with both FEA and results obtained from compression experiments. In addition there exist a good correlation between structural rigidity parameters and experimental failure loads. In contrast, there was no correlation between average bone density and failure load.

Self-similar hierarchical honeycombs

Hierarchical structures are observed in nature, and can be shown to offer superior efficiency. However, the potential advantages of structural hierarchy are not well understood. We extensively explored a bending-dominated model material (i.e. transversely loaded hexagonal honeycomb) which is susceptible to improvement by simple iterative refinement that replaces each three-edge structural node with a smaller hexagon. Using a blend of analytical and numerical techniques, both elastic and plastic properties were explored over a range of loadings and iteration parameters. A wide variety of specific stiffness and specific strengths (up to fourfold increase) were achieved. The results offer insights into the potential value of iterative structural refinement for creating low-density materials with desired properties and function.

Indentation of ellipsoidal and cylindrical elastic shells

Thin shells are found in nature at scales ranging from viruses to hens' eggs; the stiffness of such shells is essential for their function. We present the results of numerical simulations and theoretical analyses for the indentation of ellipsoidal and cylindrical elastic shells, considering both pressurized and unpressurized shells. We provide a theoretical foundation for the experimental findings of Lazarus et al. [following paper, Phys. Rev. Lett. 109, 144301 (2012)] and for previous work inferring the turgor pressure of bacteria from measurements of their indentation stiffness; we also identify a new regime at large indentation. We show that the indentation stiffness of convex shells is dominated by either the mean or Gaussian curvature of the shell depending on the pressurization and indentation depth. Our results reveal how geometry rules the rigidity of shells.

Parametric investigation of load-induced structure remodeling in the proximal femur

The process of adaptive bone remodeling can be simulated with a self-optimizing finite element method. The basic remodeling rules attempt to obtain a constant value for the strain energy per unit bone mass, by adapting density. The precise solution is dependent on the loads, initial conditions, and the parameters of the remodeling rule. While there are several investigations on developing algorithms leading to the bone density distribution in the proximal femur, these algorithms often require a large number of iterations. The aim of this study was to develop a more efficient adaptive bone remodeling algorithm, and to identify how the bone density distribution of the proximal femur was affected by parameters that govern the remodeling process. The forces at different phases of the gait cycle were applied as boundary conditions. The bone density distributions from these forces were averaged to estimate the density distribution in the proximal femur. The effect of varying the initial bone density, spatial influence function, non-linear order of the adaptive algorithm, and the influence range on the converged solution were investigated. The proposed procedure was shown to converge in a fewer number of iterations and requiring less computational time, while still generating a realistic bone density distribution. It was also shown that varying the identified parameters within reasonable upper and lower bounds had very little impact on the qualitative form of the converged solution. In contrast, the convergence rate was affected to a greater degree by variation of these parameters. In all cases, the solutions obtained are comparable with the actual density in the proximal femur, as measured by Dual-energy X-ray absorptiometry (DEXA) scans.

Wrinkling of pressurized elastic shells

We study the formation of localized structures formed by the point loading of an internally pressurized elastic shell. While unpressurized shells (such as a ping-pong ball) buckle into polygonal structures, we show that pressurized shells are subject to a wrinkling instability. We study wrinkling in depth, presenting scaling laws for the critical indentation at which wrinkling occurs and the number of wrinkles formed in terms of the internal pressurization and material properties of the shell. These results are validated by numerical simulations. We show that the evolution of the wrinkle length with increasing indentation can be understood for highly pressurized shells from membrane theory. These results suggest that the position and number of wrinkles may be used in combination to give simple methods for the estimation of the mechanical properties of highly pressurized shells.

The indentation of pressurized elastic shells: from polymeric capsules to yeast cells

Pressurized elastic capsules arise at scales ranging from the 10 m diameter pressure vessels used to store propane at oil refineries to the microscopic polymeric capsules that may be used in drug delivery. Nature also makes extensive use of pressurized elastic capsules: plant cells, bacteria and fungi have stiff walls, which are subject to an internal turgor pressure. Here, we present theoretical, numerical and experimental investigations of the indentation of a linearly elastic shell subject to a constant internal pressure. We show that, unlike unpressurized shells, the relationship between force and displacement demonstrates two linear regimes. We determine analytical expressions for the effective stiffness in each of these regimes in terms of the material properties of the shell and the pressure difference. As a consequence, a single indentation experiment over a range of displacements may be used as a simple assay to determine both the internal pressure and elastic properties of capsules. Our results are relevant for determining the internal pressure in bacterial, fungal or plant cells. As an illustration of this, we apply our results to recent measurements of the stiffness of baker's yeast and infer from these experiments that the internal osmotic pressure of yeast cells may be regulated in response to changes in the osmotic pressure of the external medium.

Protocol for constructing subject-specific biomechanical models of knee joint

A robust protocol for building subject-specific biomechanical models of the human knee joint is proposed which uses magnetic resonance imaging, motion analysis and force platform data in conjunction with detailed 3D finite element models. The proposed protocol can be used for determining stress and strain distributions and contact kinetics in different knee elements at different body postures during various physical activities. Several examples are provided to highlight the capabilities and potential applications of the proposed protocol. This includes preliminary results on the role of body weight on the stresses and strains induced in the knee articular cartilages and meniscus during single-leg stance and calculations of the induced stresses and ligament forces during the gait cycle.

Effect of frontal plane tibiofemoral angle on the stress and strain at the knee cartilage during the stance phase of gait

Subject-specific three-dimensional finite element models of the knee joint were created and used to study the effect of the frontal plane tibiofemoral angle on the stress and strain distribution in the knee cartilage during the stance phase of the gait cycle. Knee models of three subjects with different tibiofemoral angle and body weight were created based on magnetic resonance imaging of the knee. Loading and boundary conditions were determined from motion analysis and force platform data, in conjunction with the muscle-force reduction method. During the stance phase of walking, all subjects exhibited a valgus-varus-valgus knee moment pattern with the maximum compressive load and varus knee moment occurring at approximately 25% of the stance phase of the gait cycle. Our results demonstrated that the subject with varus alignment had the largest stresses at the medial compartment of the knee compared to the subjects with normal alignment and valgus alignment, suggesting that this subject might be most susceptible to developing medial compartment osteoarthritis (OA). In addition, the magnitude of stress and strain on the lateral cartilage of the subject with valgus alignment were found to be larger compared to subjects with normal alignment and varus alignment, suggesting that this subject might be most susceptible to developing lateral compartment knee OA.