Presence of Post-traumatic Limps in an Adult Population Diagnosed on a "Catwalk Video": A Comparative Study Between Healthcare and Nonhealthcare Individuals

Background Walking is an everyday activity but also complex in nature. Gait disorders have the potential to drastically affect an individual's quality of life and their ability to be independent. The causes of gait disorders are numerous. To identify abnormal gait, clinicians utilize gait analysis. The aim of this study is to assess how well individuals can identify limps in postoperative traumatized individuals with lower extremity deformities. Methods Participants observed a video compiled of individuals with various gait abnormalities and severities of limps. In the video, there were nine abnormal gait presentations, four obvious limps, and five subtle limps, while the other 10 gait presentations were normal gaits. Classifications for gait presentations were assigned by the research team. Participants assigned a classification to each limp case presented in the video on a survey. The participants were separated into two groups: those with healthcare experience and lay individuals. A Mann-Whitney U-test was used to compare healthcare experience and lay individuals' ability to identify limps correctly. In addition, the observers were evaluated on their ability to perform a screening diagnosis of a limp. Results A total of 100 participants were included in the study, 46 with healthcare experience and 54 individuals without. All tests, identification of limp and subtle limp, using the Mann-Whitney U-test yielded non-significant differences between healthcare and nonhealthcare experience. Overall lowest correctness between both groups came when attempting to identify subtle limp (healthcare = 57.39%, nonhealthcare = 56.67%) while the highest correctness yield was when identifying limp (healthcare = 96.74%, nonhealthcare = 95.37%). Analysis of the observers' ability to perform a screening diagnosis of limp provided close to gold standard results (sensitivity = 96.0%, specificity = 98.7%, positive predictive value = 99.2%, negative predictive value = 98.4%). Conclusion This study showed that nonhealthcare individuals can accurately perform gait analysis from a video, particularly in identifying the presence of a limp, to a similar extent as individuals with healthcare experience. The implementation of two-dimensional catwalk videos taken from a smartphone is beneficial due to accessibility and cost-effectiveness. It also suggested that limp diagnosis can be done as a screening test, using individuals as the screener.

Accuracy and Reliability of a Suite of Digital Measures of Walking Generated Using a Wrist-Worn Sensor in Healthy Individuals: Performance Characterization Study

BACKGROUND

Mobility is a meaningful aspect of an individual's health whose quantification can provide clinical insights. Wearable sensor technology can quantify walking behaviors (a key aspect of mobility) through continuous passive monitoring.

OBJECTIVE

Our objective was to characterize the analytical performance (accuracy and reliability) of a suite of digital measures of walking behaviors as critical aspects in the practical implementation of digital measures into clinical studies.

METHODS

We collected data from a wrist-worn device (the Verily Study Watch) worn for multiple days by a cohort of volunteer participants without a history of gait or walking impairment in a real-world setting. On the basis of step measurements computed in 10-second epochs from sensor data, we generated individual daily aggregates (participant-days) to derive a suite of measures of walking: step count, walking bout duration, number of total walking bouts, number of long walking bouts, number of short walking bouts, peak 30-minute walking cadence, and peak 30-minute walking pace. To characterize the accuracy of the measures, we examined agreement with truth labels generated by a concurrent, ankle-worn, reference device (Modus StepWatch 4) with known low error, calculating the following metrics: intraclass correlation coefficient (ICC), Pearson r coefficient, mean error, and mean absolute error. To characterize the reliability, we developed a novel approach to identify the time to reach a reliable readout (time to reliability) for each measure. This was accomplished by computing mean values over aggregation scopes ranging from 1 to 30 days and analyzing test-retest reliability based on ICCs between adjacent (nonoverlapping) time windows for each measure.

RESULTS

In the accuracy characterization, we collected data for a total of 162 participant-days from a testing cohort (n=35 participants; median observation time 5 days). Agreement with the reference device-based readouts in the testing subcohort (n=35) for the 8 measurements under evaluation, as reflected by ICCs, ranged between 0.7 and 0.9; Pearson r values were all greater than 0.75, and all reached statistical significance (P<.001). For the time-to-reliability characterization, we collected data for a total of 15,120 participant-days (overall cohort N=234; median observation time 119 days). All digital measures achieved an ICC between adjacent readouts of >0.75 by 16 days of wear time.

CONCLUSIONS

We characterized the accuracy and reliability of a suite of digital measures that provides comprehensive information about walking behaviors in real-world settings. These results, which report the level of agreement with high-accuracy reference labels and the time duration required to establish reliable measure readouts, can guide the practical implementation of these measures into clinical studies. Well-characterized tools to quantify walking behaviors in research contexts can provide valuable clinical information about general population cohorts and patients with specific conditions.

Impact of COVID-19 policies on pedestrian traffic and walking patterns

The spread of COVID-19 pandemic provoked new policies and restrictions, which had an unprecedented impact on urban mobility and traffic on local and global scales. While changes in motorized traffic were investigated and monitored throughout the recent pandemic crisis in many cities around the world, not much was done on the changes in pedestrian street-traffic and walking patterns during this time. This study aims to identify, quantify, and analyze the changes in pedestrian traffic and walking patterns induced by COVID-19 policies. The "first wave" period of COVID-19 policies in Tel-Aviv, Israel, is used as a case study in this work. The analysis includes over 116 million pedestrian movement records documented by a network of 65 Bluetooth sensors, between 1.2.2020 and 26.7.2020, with a comparison to the equivalent time in 2019 that signifies "normal" pre-COVID-19 conditions. The results show clear correlation between the various COVID-19 policy restrictions and pedestrian count. The shifts to work-from-home and closure of businesses were highly correlated with changes in walking patterns during weekdays, while distinguishing changes in commercial and residential street segments. Nevertheless, while the restrictions dramatically influenced pedestrian movement volume and time of walking, it did not significantly change where people chose to walk, signifying the essentialness of attractive streets, parks and squares for citizens living in urban areas. This study shows how policy affects walking behavior in cities, demonstrating the potential of passive crowdsourced sensing technologies to provide urban planners and decision makers an efficient tool for monitoring and evaluating pedestrian infrastructure implementation in cities.

Mini-midvastus total knee arthroplasty does not result in superior gait pattern

PURPOSE

Previous studies dealing with gait after minimally invasive surgery (MIS) total knee arthroplasty (TKA) are rare and insufficient. It was the purpose of the study to determine in a prospective, comparative setting whether MIS influences the outcome of TKA in terms of typical 3D gait parameters.

METHODS

Patients scheduled for TKA or MIS TKA were invited to participate. MIS TKA was defined as TKA with shorter skin incision, mini-midvastus arthrotomy, special instruments, and avoidance of tibiofemoral dislocation and patella eversion. All other intra- and perioperative aspects were identical for both groups. A 3D gait analysis was performed with a VICON system 1 month preoperative and 8 weeks post-operative. A multivariate analysis of variance was conducted including the main effects time (pre- and post-surgery) and surgical group and the group-by-time interaction effect.

RESULTS

Seventeen MIS TKA patients and 20 TKA patients were eligible for the final analysis. We determined neither inter-group differences nor time × group interactions for any gait variables (temporospatial, ground reaction forces, joint angles and joint moments)—except for the varus-valgus knee kinematics. In pre- to post-operative comparison, the maximum valgus sway increased in the MIS group, whereas it decreased in the conventional group (p = 0.001).

CONCLUSION

From our findings, it was concluded that MIS TKA does not result in a superior walking pattern 8 weeks post-operative. Because we previously also observed mini-midvastus MIS TKA to have equal or slightly inferior results with regard to knee scores, knee torque, radiographic outcome and tourniquet/operating time, we discontinued the procedure.

LEVEL OF EVIDENCE

Prospective comparative study, Therapy, Level II.