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Rehabilitation scientists and biomedical engineers have been investigating wheelchair propulsion biomechanics in order to prevent musculoskeletal injuries. Several studies have investigated wheelchair propulsion biomechanics; however, few have examined wheelchair propulsion stroke patterns. The purpose of this study was to characterize wheelchair propulsion stroke patterns by investigating joint accelerations, joint range of motions, wheelchair propulsion phases, and stroke efficiency. Seven experienced wheelchair users (5 males, 2 females) were filmed using a three-camera motion analysis system. Each subject pushed a standard wheelchair fitted with a force-sensing pushrim (SMARTWheel) at two speeds (1.3 and 2.2 m/s). The elbow angle was analyzed in the sagittal plane, while the shoulder joint was analyzed in the sagittal and frontal planes. Three distinctly different stroke patterns: semi-circular (SC), single looping-over-propulsion (SLOP), and double looping-over-propulsion (DLOP), were identified from the kinematic analysis. Through our analysis of these patterns, we hypothesized that SC was more biomechanically efficient than the other stroke patterns. Future studies using a larger number of subjects and strokes may reveal more significant distinctions in efficiency measures between stroke patterns. [ABSTRACT FROM AUTHOR]

Wheelchair locomotion is an important form of mobility for many individuals with spinal cord injury. However, manual wheelchair propulsion can lead to upper-limb pain and can be very inefficient. This has led investigators to apply biomechanics to the study of wheelchair use. The objectives of this study were (1) to determine the frequency content of the motion of both hands during two speeds of wheelchair propulsion, (2) to obtain the filter frequencies necessary to remove noise from wheelchair motion data, and (3) to provide signal-to-noise ratio data for wheelchair kinematics. The participants in this study were a random sample of manual wheelchair users with paraplegia caused by spinal cord injury. Subjects propelled their personal wheelchairs on a computer-controlled dynamometer at speeds of 0.9 m/s and 1.8 m/s. Motion data were collected at 60 Hz with the use of a commercial infrared marker-based system. The main outcome measures were arm motions and noise frequency spectra, filter cutoff frequencies, and signal-to-noise ratio. Our results indicate that there is no useful signal power above 6 Hz during manual wheelchair propulsion at the speeds that we analyzed. In many cases, there was no useful signal power above 4 Hz. This would indicate that the frequency content of manual wheelchair propulsion is similar to that of human gait. The mean signal-to-noise ratio varied from a high of 91 dB to a low of 21.8 dB. The signal-to-noise ratio was greatest in the x direction (along the line of progression) and lowest in the z direction (medial-lateral). Manual wheelchair propulsion kinematic data should be low-pass filtered at approximately 6 Hz for speeds at or below 1.8 m/s. The data presented in the archival literature appear to have been filtered at an appropriate frequency. [ABSTRACT FROM AUTHOR]

This technical note illustrates that some of the differences that have been reported regarding wheelchair propulsion may be due to the methods used to calculate key variables. Wheelchair ambulation is a very important form of locomotion that lacks a standard pushrim force and moment analysis system. We have developed tools for analyzing upper limb biomechanics during manual wheelchair propulsion. Among the tools is a system that allows the direct measurement of global coordinate forces Fx, Fy, Fz and corresponding moments. The analytical techniques presented here allow calculation of radial (Fr) and tangential (Ft) forces, the determination of point of force application (PFA), and the moment applied by the hand (Mhz). Our results show that the PFA can be calculated from kinetic data. Comparison of the PFA to the second metacarpophalangeal (MP) joint, calculated from kinematic data and used in previous studies, resulted in a 0.2 radian difference on average, with the PFA showing greater variation near the beginning and ending of the propulsion phase. Analysis of methods for calculating the applied tangential force showed that using the PFA provides a more accurate measurement of this force than the previous method of assuming negligible hand-moment contribution. The hand moment was compared using the calculated PFA and assuming the PFA was coincident with the second MP joint. Both methods provided similar results with a mean difference of 0.6 N.m. The methods presented in this paper provide a framework for analyzing wheelchair propulsion forces and moments. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to generate functional forms of brain injury risk curves using the National Automotive Sample System Crashworthiness Data System's (NASS-CDS) database for the years of 2001-2015. The population of interest was near-side occupants who experienced a direct head impact with an injury source located lateral to a typical seated position., Methods: Brain injuries were restricted to Abbreviated Injury Scale (AIS) 2005 Update 2008 defined concussions and internal organ injuries of the head. Near-side occupants comprised two major groups, both of which were required to have evidence of head contact (i.e., a head injury with DIRINJ = 1 and SOUCON = 1 or 2): brain injured occupants (MAIS1, MAIS2, MAIS3+) and non-brain injured occupants with some other direct contact head injury (MAIS0). Analyzed cases were required to have an indication of a reasonable crash reconstruction. Injury sources allowed within the final sample consisted of A-pillars, B-pillars, roof/roof rails, impacting vehicles/exterior objects, other components of the vehicle's side interior, and other occupants or otherwise unspecified interior objects. Risk curves for occupants with brain injury severities of MAIS0, MAIS1+, MAIS2+, and MAIS3+ were generated using multivariate stepwise logistic regressions. Investigated predictors involved vehicle change in velocity, seat belt use, principal direction of force (PDOF), and injury source type (B-pillar and side window)., Results: Multivariate stepwise logistic regressions identified significant predictors of lateral change in velocity ( dvlat ) for all injury severity categories, and side window injury source (INJSOU = 56, 57, 58, 106, and 107) for MAIS0 and MAIS1+ risk curves. Although model sensitivity decreased for more severe injury predictions, risk curves dependent on only dvlat yielded accuracies of 70% for all presented models., Conclusions: Real world crashes are often complex and lack the benefit of real time monitoring; however, NASS-CDS post-crash investigations provide data useful for injury risk prediction. Further analysis is needed to determine the effect of data confidence, injury source, and accident sequence restrictions on NASS-CDS sampling biases. The presented models likely favor a more conservative risk prediction due to the limitations of NASS-CDS data collection, AIS code conversion, and unweighted sample analysis.

Introduction: Manual wheelchair users have been found to be at risk for secondary upper extremity injuries., Purpose: The primary goal of this study was to compare shoulder strength and muscle imbalance of individuals with paraplegia to case-wise matched unimpaired controls (UC). A secondary goal was to evaluate the impact of age and neurologic level of injury (NLI) on weight-normalized strength (WNS)., Methods: The SCI group (n = 28) and the UC group (n = 28) completed bilateral shoulder isokinetic strength testing in the sagittal, frontal, and horizontal plane at 60 degrees/second using the BioDex system. Strength ratios, an indicator of muscle imbalance, were also calculated., Results: No significant difference was seen in shoulder strength or strength ratios between the SCI group and the UC group. However, NLI was significantly related to WNS on several planes in the SCI group. Therefore, we dichotomized the SCI group into equal groups based on an NLI. The Low-SCI group was significantly stronger than the High-SCI group in most planes (P < 0.05). The High-SCI group was significantly weaker than the UC in extension (P < 0.01) and a trend (P < 0.01) was seen in flexion, abduction, and external rotation. The Low-SCI group was significantly stronger in abduction than the UC., Conclusion: WNS at the shoulder correlated with NLI. It is likely that this is related to contributions of the trunk and abdominal muscles during testing, since proximal trunk strength aids in generating forces distally. This study and others of strength in individuals with paraplegia may overestimate shoulder strength.

Identifying and understanding the key biomechanical factors that exemplify the power clean can provide athletes the proper tools needed to prevail at a competitive event. Therefore, the purpose of this study was to characterize and describe ground reaction forces (Fz) during the power clean lift. Three 60-Hz motion-detecting cameras and an AMTI force plate were used to collect data from 10 collegiate weightlifting men who performed a power clean at 60 and 70% of their last competitive maximum clean. The results revealed that a greater peak force (Fz) was produced during the second pull compared with the first pull and unweighted phases in both percentage lifts. As the system weight increased from 60 to 70%, the peak force (Fz) increased for the first pull and unweighted phases and decreased during the second pull phase. Learning the proper technique of the power clean may provide athletes the basic understanding needed to be competitive in a weightlifting or sporting event.

To our knowledge, no scientific literature has examined the 3-dimensional forces acting at the knee joint during a power clean. Ten male weightlifting subjects (25.9 years, SD 3.54) performed 1 set of the power clean at 60 and 70% of their maximal collegiate level for 5 repetitions. The subjects displayed a large compressive, moderate anterior, and a small degree of lateral and medial force at the knee during both percentage lifts. The majority of these forces occurred during the second pull phase or the catching phase of the lift. Lifters with decreased weight/system weight percentages displayed a more efficient lift that placed less stress on the knees. This analysis may provide invaluable information in the assessment of weight percentages used for Olympic weightlifters throughout the training year. the power clean.

Due to the high incidence of secondary wrist injury among manual wheelchair users, recent emphasis has been placed on the investigation of wheelchair propulsion biomechanics. Accurate representation of wrist activity during wheelchair propulsion may help to elucidate the mechanisms contributing to the development of wrist injuries. Unfortunately, no consensual wrist biomechanical model has been established. In order to determine if different methodologies obtain similar results, this investigation created and compared three different wrist models: 1) a fixed joint center placed between the styloids (midstyloid joint center); 2) a joint center with 2 degrees of freedom computed from de Leva's joint center data; and 3) a floating joint center. Results indicate that wrist flexion and extension angles are highly consistent between models, however, radial and ulnar deviation angles vary considerably. Mean maximum right flexion angles were found to be 3.5 degrees, 2.2 degrees, and 5.0 degrees for the midstyloid, de Leva, and floating joint center models, respectively. Extension angles were 22.3 degrees, 23.6 degrees, and 23.6 degrees, respectively. Mean maximum right radial deviation angles for the midstyloid, de Leva, and floating joint center models were 26.0 degrees, 26.9 degrees, and 45.1 degrees, respectively, and ulnar deviation angles were found to be 30.5 degrees, 38.8 degrees, and 10.2 degrees, respectively. This information is useful when comparing kinematic studies and further supports the need for consensual methodology.

Objectives: Individuals who use manual wheelchairs are at high risk for median nerve injury and subsequent carpal tunnel syndrome (CTS). To gain a better understanding of the mechanism behind CTS in manual wheelchair users, this study examined the relation between (1) pushrim biomechanics and function of the median nerve, (2) pushrim biomechanics and subject characteristics, and (3) median nerve function and subject characteristics., Design: Case series., Setting: Biomechanics laboratory and an electromyography laboratory., Participants: Thirty-four randomly recruited individuals with paraplegia who use a manual wheelchair for mobility., Intervention: Subjects propelled their own wheelchair on a dynamometer at 0.9m/sec and 1.8m/sec. Bilateral biomechanical data were obtained using a force- and moment-sensing pushrim and a motion analysis system. Bilateral nerve conduction studies focusing on the median nerve were also completed., Main Outcome Measures: Pearson's correlation coefficients between subject characteristics, median nerve conduction studies, and propulsion biomechanics; a regression model of nerve conduction studies incorporating subject characteristics and pushrim biomechanics., Results: Subject weight was significantly related to median nerve latency (r = .36, p = .03) and median sensory amplitude (r = -.43, p = .01). Height was also significantly related to median sensory amplitude (r = -.58, p = .01). Subject weight was significantly related to the peak resultant force applied to the pushrim (r = .59, p < .001). Height, weight, and weight-normalized pushrim forces were successfully incorporated into a linear regression model predicting median sensory amplitude (r = .63, p < .05) and mean median latency (r = .54, p < .05)., Conclusion: This study found subject weight to be related to pushrim forces and median nerve function. Independent of subject weight, pushrim biomechanics were also related to median nerve function. Through weight loss and changes in pushrim biomechanics, it may be possible to prevent median nerve injury in manual wheelchair users.

Individuals who propel wheelchairs have a high prevalence of upper extremity injuries. To better understand the mechanism behind these injuries this study investigates the motion of the shoulder and elbow during wheelchair propulsion. The objectives of this study are: (1) To describe the motion occurring at the shoulder and elbow in anatomical terms during wheelchair propulsion; (2) to obtain variables that characterize shoulder and elbow motion and are statistically stable; (3) to determine how these variables change with speed. The participants in the study were a convenience sample of Paralympic athletes who use manual wheelchairs for mobility and have unimpaired arm function. Each subject propelled an ultralight wheelchair on a dynamometer at 1.3 and 2.2 meters per second (m/s). Biomechanical data was obtained using a force and moment sensing pushrim and a motion analysis system. The main outcome measures investigated were: maximum and minimum angles while in contact with the pushrim, range of motion during the entire stroke and peak accelerations. All of the measures were found to be stable at both speeds (Cronbach's alpha > 0.8). The following measures were found to differ with speed (data format: measure at 1.3 m/s +/- SD; measure at 2.2 m/s +/- SD): minimum shoulder abduction angle during propulsion (24.5 degrees +/- 6.7, 21.6 degrees +/- 7.2), range of motion during the entire stroke in elbow flexion/extension (54.0 degrees +/- 9.9, 58.1 degrees +/- 10.4) and shoulder sagittal flexion/extension (74.8 degrees +/- 9.4, 82.6 degrees +/- 8.5), and peak acceleration in shoulder sagittal flexion/extension (4044 degrees/s2 +/- 946, 7146 degrees/s2 +/- 1705), abduction/adduction (2678 degrees/s2 +/- 767, 4928 degrees/s2 +/- 1311), and elbow flexion/extension (9355 degrees/s2 +/- 4120, 12889 degrees/s2 +/- 5572). This study described the motion occurring at the shoulder and elbow using a local coordinate system. Stable parameters that characterize the propulsive stroke and differed with speed were found. In the future these same parameters may provide insight into the cause and prevention of shoulder and elbow injuries in manual wheelchair.

The measurement of the center of pressure (COP) has been and continues to be a successful tool for gait analysis. The definition of a similar COP for wheelchair propulsion. however, is not straightforward. Previously, a COP definition similar to that used in force plate analysis had been proposed. Unfortunately, this solution has the disadvantage of requiring a separate COP definition for each plane of analysis. A definition of the generalized center of pressure (GCOP) which is consistent in all planes of analysis is derived here. This definition is based on the placement of a force-moment system, equivalent to the force-moment system at the hub, on a line in space where the moment vector (wrench moment) is parallel to the force vector. The parallel force-moment system is then intersected with three planes defined by anatomical landmarks on the hand. Data were collected using eight subjects at propulsion speeds of 1.34 m/s and 2.24 m/s (1.34 m/s only for subject 1, 0.894 m/s and 1.79 m/s for subject 8). Each subject propelled a wheelchair instrumented with a SMARTwheel. A PEAK 5 video system was used to determine the position of anatomical markers attached to each subject's upper extremity. The GCOP in the transverse plane of the wrist formed clusters for all subject's except subject 2 at 1.34 m/s. The clustering of the GCOP indicates that the line of action for the force applied by the hand is approximately perpendicular to the transverse plane through the wrist. When comparing the magnitude of the moment vector part of the wrench with the moment of the force vector of the wrench about the hub, the wrench moment is approximately an order of magnitude smaller. This indicates that the role of the wrist for wheelchair propulsion is primarily to stabilize the force applied by the arm and shoulder.

Wheelchair propulsion kinetic measurements require the use of custom pushrim force/moment measuring instruments which are not currently commercially available. With the ability to measure pushrim forces and moments has come the development of several dynamic metrics derived for analyzing key aspects of wheelchair propulsion. This paper presents several of the equations used to calculate or derive the primary variables used in the study of wheelchair propulsion biomechanics. The uncertainties for these variables were derived, and then numerically calculated for a current version of the SMARTWheel. The uncertainty results indicate that the SMARTWheel provides data which has better than 5 to 10% uncertainty, depending upon the variable concerned, at the maximum, and during most of the propulsion phase the uncertainty is considerably smaller (i.e., approximately 1%). The uncertainty analysis provides a more complete picture of the attainable accuracy of the SMARTWheel and of the degree of confidence with which the data can be recorded. The derivations and results indicate where improvements in measurement of wheelchair propulsion biomechanical variables are likely to originate. The most efficient approach is to address those variables in the design of the system which make the greatest contribution to the uncertainty. Future research will focus on the point of force application and examination of nonlinear effects.

The objective of this study was to develop and test a method for projecting the pushrim point of force application (PFA) onto a palmar plane model of the hand. Repetitive wheelchair use often leads to hand and wrist pain or injury. The manner by which the hands grasp the pushrim and how the forces and moments applied to the pushrim are directed may contribute to the high incidence of pain and injury. The projections of the PFA onto the palmar surface model of the hand reside primarily within zone II. These results are in agreement with previous studies which have assumed the PFA to be coincident with one of the metacarpophalangeal (MP) joints. However, the results from three subjects show different PFA patterns within the palmar surface of the hand which can be related to each subject's propulsion pattern, and the PFA is not focused at a single MP joint. Projection of the world coordinates of the four hand marker system onto the palmar plane show the resolution to be within 3 mm, or one half the diameter of the passive reflective markers. The errors in the planar model assumption were greatest for the second and fifth MP markers. This was expected because as the hand grasp changes these markers do not remain coplanar. The results of this study indicate that new knowledge about how forces are applied by the hand onto the pushrim can be obtained using this method. This technical note provides insight into understanding the details within the kinetics of wheelchair propulsion and describes a technique for estimation of the PFA on the palmar surface of the hand. This technical note provides initial results from three different wheelchair users.

Objective: To investigate pushrim forces and joint kinetics during wheelchair propulsion and to discuss the differences between inexperienced and experienced wheelchair users., Design: Cohort study., Setting: Human engineering laboratory at a state university., Subjects: Four men who use manual wheelchairs for mobility and four nondisabled men who did not have extensive experience pushing a wheelchair; all subjects were asymptomatic for upper extremity pain or injury., Methods: Subjects pushed a commonly used wheelchair fitted with a force-sensing pushrim on a stationary wheelchair dynamometer. Video and force data were collected for 5 strokes at one speed of propulsion. Pushrim forces and net joint forces and moments were analyzed., Main Outcome Measures: Pushrim forces, radial (Fr) and tangential (Ft), were analyzed and compared for both groups in relation to peak values and time to peak values and as ratios of overall forces generated. Net joint forces and moments were analyzed in a similar fashion., Results: Pushrim forces and joint moments were similar to those previously reported, with radial forces averaging between 34 and 39N and tangential forces ranging on average between 66 and 95N. Tangential forces were higher than radial forces, and mean ratios of tangential forces to the resultant force were approximately 75%, whereas mean radial force ratios were approximately 22%. All subjects showed higher joint moments at the shoulder than at the elbow or wrist. A large component of vertical reaction force was seen at the shoulder. Significant differences (p < .05) were found between groups for peak tangential force and time to peak tangential and peak vertical forces, with wheelchair users having lower values and longer times to reach the peak values., Conclusions: Discrete variables from the force-time curves can be used to distinguish between wheelchair users and nonusers. The experienced users tended to push longer, used forces with lower peaks, and took longer time to reach peak values. This propulsive pattern may have been developed to reduce the chance of injury by minimizing the forces at the joints, as a means of maximizing efficiency or as a combination of these factors. More work investigating 3-dimensional forces and the influence of seating position and various conditions of propulsion such as speed changes, ramps, and directional changes on injury mechanisms needs to be completed.