Restricting lumbar spine flexion redistributes and changes total mechanical energy expenditure during lifting.

Minimizing lumbar spine flexion during lifting requires greater lower extremity joint motion. However, the effects of these kinematic changes on lumbar and lower extremity joint kinetics are unknown. Further, it is unclear whether the distribution of biomechanical demands throughout the lumbar spine and lower extremity during lumbar spine flexion restricted lifting are modulated by task factors like lift origin height and object mass. This study examined the influence of restricting lumbar spine flexion during lifting on the distribution of biomechanical demands, operationalized as mechanical energy expenditure (MEE), across the lumbar spine and lower extremity joints during lifting tasks. Twenty participants performed a series of lifting tasks that varied by lift origin height, object mass and presence or absence of lumbar spine motion restricting harness. MEE was quantified for the lumbar spine and lower extremity joints and summed across all joints to represent the total MEE. Distributions of MEE were compared across combinations of the three task factors. Total MEE was greater when lifting with restricted spine motion (p < 0.001). MEE was redistributed away from the lumbar spine and predominantly to the hips in the spine restricted conditions (p < 0.001). The nature and magnitude of this effect was modulated by lift origin height for the lumbar spine (p < 0.001) and hips (p < 0.001). Findings demonstrated that biomechanical demands can be shifted from the lumbar spine to the lower extremity when lifting with restricted spine flexion, which might help mitigate overuse injuries through coordinative variability.

Estimation of lower back muscle force in a lifting task using wearable IMUs.

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

Equivalent weight: Application of the assessment method on real task conducted by railway workers wearing a back support exoskeleton.

Commonly used risk indexes, such as the NIOSH Lifting Index, do not capture the effect of exoskeletons. This makes it difficult for Health and Safety professionals to rigorously assess the benefit of such devices. The community requires a simple method to assess the effectiveness of back-support exoskeleton's (BSE) in possibly reducing ergonomic risk. The method introduced in this work is termed "Equivalent Weight" (EqW) and it proposes an interpretation of the effect built on the benefit delivered through reduced activation of the erector spinae (ES). This manifests itself as an apparent reduction of the lifted load perceived by the wearer. This work presents a pilot study where a practical application of the EqW method is used to assess the ergonomic risk in manual material handling (MMH) when using a back support exoskeleton (StreamEXO). The results are assessed by combining observational measurements from on-site testing with five different workers and quantitative measures of the muscle activity reduction achieved during laboratory evaluation with ten workers. These results will show that when lifting, lowering, and carrying a 19 kg load the StreamEXO can reduce risk by up to two levels (from "high" to "low") in the target sub-tasks. The Lifting index (LI) was reduced up to 64% when examining specific sub-tasks and the worker's movement conduction.

Biomechanical analysis of different back-supporting exoskeletons regarding musculoskeletal loading during lifting and holding.

Industrial back support exoskeletons (BSEs) are a promising approach to addressing low back pain (LBP) which still affect a significant proportion of the workforce. They aim to reduce lumbar loading, the main biomechanical risk factor for LBP, by providing external support to the lumbar spine. The aim of this study was to determine the supporting effect of one active (A1) and two passive (P1 and P2) BSEs during different manual material handling tasks. Kinematic data and back muscle activity were collected from 12 subjects during dynamic lifting and static holding of 10 kg. Mean and peak L5/S1 extension moments, L5/S1 compression forces and muscle activation were included in the analysis. During dynamic lifting all BSEs reduced peak (12-26 %) and mean (4-17 %) extension moments and peak (10-22 %) and mean (4-15 %) compression forces in the lumbar spine. The peak (13-28 %) and mean (4-32 %) activity of the back extensor muscles was reduced accordingly. In the static holding task, analogous mean reductions for P1 and P2 of L5/S1 extension moments (12-20 %), compression forces (13-23 %) and muscular activity (16-23 %) were found. A1 showed a greater reduction during static holding for extension moments (46 %), compression forces (41 %) and muscular activity (54 %). This pronounced difference in the performance of the BSEs between tasks was attributed to the actuators used by the different BSEs.

Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results.

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment.

Estimating Compressive and Shear Forces at L5-S1: Exploring the Effects of Load Weight, Asymmetry, and Height Using Optical and Inertial Motion Capture Systems.

This study assesses the agreement of compressive and shear force estimates at the L5-S1 joint using inertial motion capture (IMC) within a musculoskeletal simulation model during manual lifting tasks, compared against a top-down optical motion capture (OMC)-based model. Thirty-six participants completed lifting and lowering tasks while wearing a modified Plug-in Gait marker set for the OMC and a full-body IMC set-up consisting of 17 sensors. The study focused on tasks with variable load weights, lifting heights, and trunk rotation angles. It was found that the IMC system consistently underestimated the compressive forces by an average of 34% (975.16 N) and the shear forces by 30% (291.77 N) compared with the OMC system. A critical observation was the discrepancy in joint angle measurements, particularly in trunk flexion, where the IMC-based model underestimated the angles by 10.92-11.19 degrees on average, with the extremes reaching up to 28 degrees. This underestimation was more pronounced in tasks involving greater flexion, notably impacting the force estimates. Additionally, this study highlights significant differences in the distance from the spine to the box during these tasks. On average, the IMC system showed an 8 cm shorter distance on the X axis and a 12-13 cm shorter distance on the Z axis during lifting and lowering, respectively, indicating a consistent underestimation of the segment length compared with the OMC system. These discrepancies in the joint angles and distances suggest potential limitations of the IMC system's sensor placement and model scaling. The load weight emerged as the most significant factor affecting force estimates, particularly at lower lifting heights, which involved more pronounced flexion movements. This study concludes that while the IMC system offers utility in ergonomic assessments, sensor placement and anthropometric modeling accuracy enhancements are imperative for more reliable force and kinematic estimations in occupational settings.

Hip osteoarthritis and occupational mechanical exposures: a systematic review and meta-analysis.

OBJECTIVES: The aim was to conduct a systematic review and meta-analysis investigating the association between occupational mechanical exposures and hip osteoarthritis. METHODS: The study was registered in PROSPERO. A systematic literature search was conducted in six databases to identify relevant articles. Two authors independently excluded articles, extracted data, assessed the risk of bias of each included article, and graded the level of evidence. We conducted a meta-analysis using random-effects model and performed a sensitivity analysis stratifying articles based on the risk of bias assessment, study design, and the outcome measurement. RESULTS: Twenty-four articles were eligible for inclusion. The highest pooled odds ratio (OR) was found for combined mechanical exposures [OR 1.7, 95% confidence interval (CI) 1.4-2.0], non-neutral postures (OR 1.7, 95% CI 1.4-2.1), lifting/carrying loads (OR 1.6, 95% CI 1.3-1.9), and climbing stairs (OR 1.6, 95% CI 1.1-2.2). The range of pooled OR for the remaining mechanical exposures (eg, standing, walking, kneeling, squatting, and sitting) was 0.6-1.6. Grading the quality of evidence, a moderate level of evidence was found for the combined mechanical exposures and for lifting/carrying loads. The remaining exposure categories were graded as having either low or very low levels of evidence. CONCLUSIONS: Considerable heterogeneity was observed across the included studies, and high-quality literature using objective exposure measurements is warranted. Despite various limitations affecting the comparability, occupational mechanical exposures seem to influence the likelihood of developing hip osteoarthritis.

Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain.

Machine learning (ML) algorithms are crucial within the realm of healthcare applications. However, a comprehensive assessment of the effectiveness of regression algorithms in predicting alterations in lifting movement patterns has not been conducted. This research represents a pilot investigation using regression-based machine learning techniques to forecast alterations in trunk, hip, and knee movements subsequent to a 12-week strength training for people who have low back pain (LBP). The system uses a feature extraction algorithm to calculate the range of motion in the sagittal plane for the knee, trunk, and hip and 12 different regression machine learning algorithms. The results show that Ensemble Tree with LSBoost demonstrated the utmost accuracy in prognosticating trunk movement. Meanwhile, the Ensemble Tree approach, specifically LSBoost, exhibited the highest predictive precision for hip movement. The Gaussian regression with the kernel chosen as exponential returned the highest prediction accuracy for knee movement. These regression models hold the potential to significantly enhance the precision of visualisation of the treatment output for individuals afflicted with LBP.

Determining whether biomechanical variables that describe common 'safe lifting' cues are associated with low back loads.

Lift technique training programs have been implemented to help reduce injury risk, but the underlying content validity of cues used within these programs is not clear. The objective of this study was to determine whether biomechanical variables, that commonly used lifting cues aim to elicit, are associated with resultant low back extensor moment exposures. A sample of 72 participants were recruited to perform 10 repetitions of a floor-to-waist height barbell lift while whole-body kinematics and ground reaction forces were collected. Kinematic, kinetic, and energetic variables representative of characteristics commonly targeted by lifting cues were calculated as predictor variables, while peak and cumulative low back moments were calculated as dependent measures. Multiple regression revealed that 56.6-59.2% of variance in low back moments was explained by predictor variables. From these regression models, generating motion with the legs (both greater hip and knee work), minimizing the horizontal distance of the body to the load, maintaining a stable body position, and minimizing lift time were associated with lower magnitudes of low back moments. These data support that using cues targeting these identified variables may be more effective at reducing peak low back moment exposures via lift training.

Effect of low back pain on the kinetics and kinematics of the lumbar spine - a combined in vivo and in silico investigation.

Lifting is a significant risk factor for low back pain (LBP). Different biomechanical factors including spinal loads, kinematics, and muscle electromyography (EMG) activities have previously been investigated during lifting activities in LBP patients and asymptomatic individuals to identify their association with LBP. However, the findings were contradictory and inconclusive. Accurate and subject-specific prediction of spinal loads is crucial for understanding, diagnosing, planning tailored treatments, and preventing recurrent pain in LBP patients. Therefore, the present study aimed to estimate the L5-S1 compressive and resultant shear loads in 19 healthy and 17 non-specific chronic LBP individuals during various static load-holding tasks (holding a 10 kg box at hip, chest, and head height) using full-body and personalized musculoskeletal models driven by subject-specific in vivo kinematic/kinetic, EMG, and physiological cross-sectional areas (PCSAs) data. These biomechanical characteristics were concurrently analyzed to identify potential differences between the two groups. Statistical analyses showed that LBP had almost no significant effect on the range of motion (trunk, lumbar, pelvis), PCSA, and EMG. There were no significant differences (p > 0.05) in the predicted L5-S1 loads. However, as the task became more demanding, by elevating the hand-load from hip to head, LBP patients experienced significant increases in both compressive (33 %, p = 0.00) and shear (25 %, p = 0.02) loads, while asymptomatic individuals showed significant increases only in compressive loads (30 %, p = 0.01). This suggests that engaging in more challenging activities could potentially magnify the effect of LBP on the biomechanical factors and increase their discrimination capacity between LBP and asymptomatic individuals.

Conventional video recordings dependably quantify whole-body lifting strategy using the Stoop-Squat-Index: A methods comparison against motion capture and a reliability study.

Whole-body lifting strategies could be derived from conventional video recordings using the Stoop-Squat-Index, which quantifies the ratio between trunk forward lean and lower extremity joint flexion from 0 (full squat) to 100 (full stoop). The purpose of this study was to compare Stoop-Squat-Indices derived from conventional video recordings to those from a three-dimensional marker-based motion capture system and to evaluate interrater and intrarater reliability of the video-based approach. Thirty healthy participants lifted a 5-kg box under different conditions (freestyle, squat, stoop). Kinematic data were recorded using a Vicon motion capture system (serving as reference standard) and an iPad camera. Stoop-Squat-Indices over the entire lifting cycle were derived separately from both approaches. Agreement was assessed using mean differences (video minus motion capture) and limits of agreement. Reliability was investigated by calculating intraclass correlation coefficients (ICC) and minimal detectable changes (MDC) over the course of the lifting cycle. Systematic errors were identified with Statistical Parametric Mapping-based T-tests. Systematic errors between the video-based and the motion capture-based approach were observed among all conditions. Mean differences in Stoop-Squat-Indices over the lifting cycle ranged from -6.9 to 3.2 (freestyle), from -1.8 to 5.3 (squat) and from -2.8 to -1.1 (stoop). Limits of agreement were lower when the box was close to the floor, and higher towards upright standing. Reliability of the video-based approach was excellent for most of the lifting cycle, with ICC above 0.995 and MDC below 3.5. These findings support using a video-based assessment of Stoop-Squat-Indices to quantify whole-body lifting strategy in field.

Electromyography-driven musculoskeletal models with time-varying fatigue dynamics improve lumbosacral joint moments during lifting.

Muscle fatigue is prevalent across different aspects of daily life. Tracking muscle fatigue is useful to understand muscle overuse and possible risk of injury leading to musculoskeletal disorders. Current fatigue models are not suitable for real-world settings as they are either validated using simulations or non-functional tasks. Moreover, models that capture the changes to muscle activity due to fatigue either assume a linear relationship between muscle activity and muscle force or utilize a simple muscle model. Personalised electromygraphy (EMG)-driven musculoskeletal models (pEMS) offer person-specific approaches to model muscle and joint kinetics during a wide repertoire of daily life tasks. These models utilize EMG, thus capturing central fatigue-dependent changes in multi-muscle bio-electrical activity. However, the peripheral muscle force decay is missing in these models. Thus, we studied the influence of fatigue on a large scale pEMS of the trunk. Eleven healthy participants performed functional asymmetric lifting task. Average peak body-weight normalized lumbosacral moments (BW-LM) were estimated to be 2.55 ± 0.26 Nm/kg by reference inverse dynamics. After complete exhaustion of the lower back, the pEMS overestimated the peak BW-LM by 0.64 ± 0.37 Nm/kg. Then, we developed a time-varying muscle force decay model resulting in a time-varying pEMS (t-pEMS). This reduced the difference between BW-LM estimated by the t-pEMS and reference to 0.49 ± 0.14 Nm/kg. We also showed that five fatiguing contractions are sufficient to calibrate the t-pEMS. Thus, this study presents a person and muscle specific model to track fatigue during functional tasks.

Recent Advancements in Pectus Surgery: Crane Lifting, Multiple-Bar Approach, Bridge Stabilization, and Sandwich Technique.

PURPOSE: The most recent procedure for pectus excavatum repair involves crane-powered entire chest wall remodeling, which employs crane lifting, multiple-bar approach, bridge stabilization, and sandwich techniques. This resulted in a paradigm shift in pectus deformity repair from merely lifting the sunken bone to remodeling the chest wall into normal anatomy. METHODS: We analyzed 649 patients who underwent surgery for pectus excavatum or complex combined deformities between March 2018 and January 2022. A crane with sternal wiring or screwing was used to lift the chest wall without using the pectus bar turning power. Multiple bars with bridge connections were placed to eliminate bar displacement. Modified sandwich techniques were applied to relieve the lower coastal flare (flare-buster) and focal protuberance (magic string). RESULTS: The mean age of the patients included in the study was 12.2 years (range: 3-45 years). A single bar was used for 202 patients until 2021. For the multiple-bar technique, parallel bars (n = 142), crossbars (n = 166), and crossbars plus upper horizontal bars (XI pattern; n = 139) were used. The overall complication rate was 6.2 %. There was no cases of bar displacement were observed, but other minor complications such as pneumothorax (n = 20, 3.1 %), pleural effusion (n = 7, 1.1 %), and wound infection (n = 5, 0.8 %) were detected. Three patients required reoperation (infection, two: hemorrhage, one). CONCLUSIONS: The crane-powered entire chest wall remodeling technique improved the safety and comprehensiveness of the repair procedure. By incorporating bridge stabilization and the use of multiple bars, we effectively resolved the issues related to bar displacement and incomplete repair. TYPE OF STUDY: Retrospective Cohort Study.

Long-Term Improvement of Crow's Feet Wrinkles in Combination With Cervicofacial and Temporal Lifting: Review of the Literature.

BACKGROUND: The lateral orbital crow's feet area is one for which rejuvenation is most frequently requested by patients. Moreover, lateral canthal wrinkles are a common source of dissatisfaction after rhytidoplasty. Botulinum toxin injection has emerged as a most popular, easy, and effective solution; nevertheless, repeated injections are required periodically for long-term effect. Other nonsurgical options have also been described to have some demonstrable advantages. Orbicularis oculi surgical manipulations have been described as well. MATERIAL AND METHODS: A systematic PubMed literature search was conducted to identify clinical cohort studies including more than 10 patients describing surgical approaches for improvement of crows' feet wrinkles in combination with face and/or temporal lifts. The search was complemented by Embase, Medline, and Cochrane searches in addition to screening of reference lists of selected studies and simple term searches about surgical treatment of crow's feet. RESULTS: Fourteen studies satisfied the inclusion criteria and were included in this review describing various muscle excision techniques including vertical strip excision, lateral partial resection, wedge resection, muscle resection in "C" pattern, and enlarged myectomy of about one-third of the whole orbital extension in addition to muscle manipulation modalities, including muscle splaying, muscle division, muscle division and splaying, muscle undermining with partial denervation, and muscle suspension. Interposition of fascia between orbicularis muscle and overlying skin was also reported. CONCLUSION: View the few studies retrieved and the wide spectrum of reported techniques, it is not possible to determine from this review the most effective modality. Nevertheless, it seems that subcutaneous undermining of the lateral canthal area combined with splaying and traction of the orbicularis oculi muscle and fixation to the temporalis fascia with or without muscle division would yield the best long-term results. This review indicates also that surgical correction of crow's feet during rhytidectomy or temporal lift could be a positive complement to improve aesthetic outcome. Unfortunately, if not underreported, it is definitely neglected. We believe that this review may be an eye-opener for surgeons.

In vivo load on knee, hip and spine during manual materials handling with two lifting techniques.

It is generally accepted that the lifting technique strongly influences physical loads within the human body and, thus, the risk of musculoskeletal disorders. However, there is a lack of knowledge regarding whether particular lifting techniques are effective in reducing loads. Hence, this retrospective study quantified (partly published) in vivo loads at joints within the human body during two typical lifting techniques, stoop lifting and squat lifting. Patients who had received instrumented implants underwent in vivo load measurements at either the knee (two patients), the hip (eight patients), or the upper lumbar spine (four patients) while lifting a 10 kg weight frontally with either straight (stoop) or bent (squat) knees. Contact forces and moments and the orientation of the contact force vector were determined and examined using the paired t test of Statistical Parametric Mapping. The two lifting techniques did not differ in terms of load magnitudes but did differ in terms of directions: (i) at the hip joint, the load vector varied significantly (p < 0.05) in the frontal and sagittal planes, (ii) at the knee joint, the load vector differed significantly (p < 0.05) in the sagittal plane (iii) while the load vector and magnitude did not differ at the upper lumbar spine (p > 0.05). Our findings indicate that the lifting technique causes changes in the orientation rather than the magnitude of lower extremity joint contact loads. Even though this quantification could only be performed in a small group of patients, the quantification of the relevance of such lifting technique recommendations will hopefully guide future recommendations towards a more scientific interpretation.

Exploring how metronome pacing at varying movement speeds influences local dynamic stability and coordination variability of lumbar spine motion during repetitive lifting.

Auditory metronomes have been used to preserve movement consistency when examining local dynamic stability (LDS) and coordination variability (CV) of lumbar spine motion during repetitive movements. However, the potential influence of the metronome itself on these outcome measures has rarely been considered. Therefore, this study investigated the influence of different metronome paces (i.e., lifting speeds) on measures of lumbar spine LDS and thorax-pelvis CV during a repetitive lifting/lowering task in comparison to self-paced movements. Ten participants completed 5 repetitive lift/lower trials, where participants completed 35 consecutive repetitions (analysis on last 30 repetitions) at a self-selected pace for the first and last trial, and were paced by a 10 lift/min, 15 lift/min, and 20 lift/min metronome, in randomized order, for the remaining three trials. The average self-paced lift/lower speed before and after experiencing the three different metronome paced speeds was 16.2 (±1.02) and 17.2 (±0.73) lifts/min, respectively, and the most-preferred metronome pace trial was 15 lifts/min. Thorax-pelvis CV during the self-paced trials were similar (p > 0.05) to the 15 lift/min metronome paced trials, while greater thorax-pelvis CV was observed for the 10 lift/min compared to the 15 lift/min and 20 lift/min and second self-paced trial (all p < 0.026). This movement speed effect was not observed for lumbar spine LDS; however, more-dynamically stable movements were observed during all metronome paced trials in comparison to the self-paced trials. This study highlights that careful consideration is required when employing a metronome to control/manipulate movement characteristics while examining neuromuscular control using non-linear dynamical systems measures.

An artificial neural network for full-body posture prediction in dynamic lifting activities and effects of its prediction errors on model-estimated spinal loads.

Musculoskeletal models have indispensable applications in occupational risk assessment/management and clinical treatment/rehabilitation programs. To estimate muscle forces and joint loads, these models require body posture during the activity under consideration. Posture is usually measured via video-camera motion tracking approaches that are time-consuming, costly, and/or limited to laboratories. Alternatively, posture-prediction tools based on artificial intelligence can be trained using measured postures of several subjects performing many activities. We aimed to use our previous posture-prediction artificial neural network (ANN), developed based on many measured static postures, to predict posture during dynamic lifting activities. Moreover, effects of the ANN posture-prediction errors on dynamic spinal loads were investigated using subject-specific musculoskeletal models. Seven individuals each performed twenty-five lifting tasks while their full-body three-dimensional posture was measured by a 10-camera Vicon system and also predicted by the ANN as functions of the hand-load positions during the lifting activities. The measured and predicted postures (i.e., coordinates of 39 skin markers) and their model-estimated L5-S1 loads were compared. The overall root-mean-squared-error (RMSE) and normalized (by the range of measured values) RMSE (nRMSE) between the predicted and measured postures for all markers/tasks/subjects was equal to 7.4 cm and 4.1 %, respectively (R2 = 0.98 and p < 0.05). The model-estimated L5-S1 loads based on the predicted and measured postures were generally in close agreements as also confirmed by the Bland-Altman analyses; the nRMSE for all subjects/tasks was < 10 % (R2 > 0.7 and p > 0.05). In conclusion, the easy-to-use ANN can accurately predict posture in dynamic lifting activities and its predicted posture can drive musculoskeletal models.

Evaluating the impact of lifting mandatory smoking cessation prior to elective abdominal wall reconstruction. A single-center experience.

INTRODUCTION: Many studies identify active smoking as a significant risk factor for postoperative wound and mesh complications in patients undergoing abdominal wall reconstruction surgery. However, our group conducted an analysis using data from the ACHQC database, which revealed similar rates of surgical site infection (SSI) and surgical site occurrence requiring procedural intervention (SSOPI) between active smokers and non-smokers As a result, the Cl eveland Clinic Center for Abdominal Core Health instituted a policy change where active smokers were no longer subject to surgical delay. Our study aims to evaluate the impact of active smoking on the outcomes of these patients. METHODS: We identified active smoking patients who had undergone open, elective, clean ventral hernia repair (VHR) with transversus abdominis release (TAR) and permanent synthetic mesh at Cleveland Clinic Foundation. Propensity matching was performed to create a 1:3 ratio of "current-smokers" and "never-smokers" and compared wound complications and all 30-day morbidity between the two groups. RESULTS: 106 current-smokers and 304 never-smokers were matched. Demographics were similar between the two groups after matching, with the exception of chronic obstructive pulmonary disease (COPD) (22.1% vs. 13.4%, p â€‹< â€‹.001) and body mass index (BMI) (31.1 vs. 32.6, p â€‹= â€‹.02). Rates of SSI (12.2% vs. 6.9%, p â€‹= â€‹.13), SSO (21.7% vs. 13.2%, p â€‹= â€‹.052), SSOPI (11.3% vs. 6.3%, p â€‹= â€‹.13), and reoperation (1.9% vs. 3.9%, p â€‹= â€‹.53) were not significantly different between active smokers and never-smokers correspondingly. One case (0.3%) of partial mesh excision was observed in the never-smokers group (p â€‹= â€‹1). The current-smokers group exhibited a significantly higher incidence of pneumonia compared to the never-smokers group (5.7% vs. 0.7%, p â€‹= â€‹.005). CONCLUSION: Our study revealed that operating on active smokers did result in a slight increase in wound morbidity, although it did not reach statistical significance. Additionally, pulmonary complications were higher in the smoking group. Notably, we did not see any mesh infections in the smoking group during early follow up. We believe that this data is important for shared decision making on patients that are actively smoking contemplating elective hernia repair.

Flexible sensor-based biomechanical evaluation of low-back exoskeleton use in lifting.

This study aimed to establish an ambulatory field-friendly system based on miniaturised wireless flexible sensors for studying the biomechanics of human-exoskeleton interactions. Twelve healthy adults performed symmetric lifting with and without a passive low-back exoskeleton, while their movements were tracked using both a flexible sensor system and a conventional motion capture (MoCap) system synchronously. Novel algorithms were developed to convert the raw acceleration, gyroscope, and biopotential signals from the flexible sensors into kinematic and dynamic measures. Results showed that these measures were highly correlated with those obtained from the MoCap system and discerned the effects of the exoskeleton, including increased peak lumbar flexion, decreased peak hip flexion, and decreased lumbar flexion moment and back muscle activities. The study demonstrated the promise of an integrated flexible sensor-based system for biomechanics and ergonomics field studies as well as the efficacy of exoskeleton in relieving the low-back stress associated with manual lifting.

This study established and tested a flexible sensor-based ambulatory system for biomechanical evaluation of human-exoskeleton interactions and as a promising new tool for field ergonomics studies in practical or naturalistic settings.Abbreviations: MoCap: motion capture; WMSD: Work-related musculoskeletal disorders; EMG: electromyography; IMU: inertial measurement unit; TES: thoracic erector spinae; LES: lumbar erector spinae; WITH: tasks performed with wearing the exoskeleton; WITHOUT: tasks performed without wearing the exoskeleton; RMS: root mean square; RMSE: root-mean-square error; r: Pearson's correlation coefficient; ASIS: anterior superior iliac spine.

Effect of muscular fatigue on the cumulative lumbar damage during repetitive lifting task: a comparative study of damage calculation methods.

Several methods have been put forward to quantify cumulative loads; however, limited evidence exists as to the subsequent damages and the role of muscular fatigue. The present study assessed whether muscular fatigue could affect cumulative damage imposed on the L5-S1 joint. Trunk muscle electromyographic (EMG) activities and kinematics/kinetics of 18 healthy male individuals were evaluated during a simulated repetitive lifting task. A traditional EMG-assisted model of the lumbar spine was modified to account for the effect of erector spinae fatigue. L5-S1 compressive loads for each lifting cycle were estimated based on varying (i.e. actual), fatigue-modified, and constant Gain factors. The corresponding damages were integrated to calculate the cumulative damage. Moreover, the damage calculated for one lifting cycle was multiplied by the lifting frequency, as the traditional approach. Compressive loads and the damages obtained through the fatigue-modified model were predicted in close agreement with the actual values. Similarly, the difference between actual damages and those driven by the traditional approach was not statistically significant (p = 0.219). However, damages based on a constant Gain factor were significantly greater than those based on the actual (p = 0.012), fatigue-modified (p = 0.017), and traditional (p = 0.007) approaches.Practitioner summary: In this study, we managed to include the effect of muscular fatigue on cumulative lumbar damage calculations. Including the effect of muscular fatigue leads to an accurate estimation of cumulative damages while eliminating computational complexity. However, using the traditional approach also appears to provide acceptable estimates for ergonomic assessments.