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Introduction: Parkinson’s disease (PD) is characterized by an alteration of the walking gait, frequently including a slower self-selected walking speed (SSWS). Although the reduction of walking speed is inherent to people with PD, such speed reduction also represents a potential confounding factor that might partly explain the observed gait differences between PD and control participants. Methods: In this study, each participant walked along a 25 m level corridor during which vertical ground reaction force signals were recorded using shoes equipped with eight pressure sensors. Vertical ground reaction force signals (using statistical parametric mapping) and temporal and kinetic variables as well as their related variability and asymmetry (using Student’s t-test) were compared between PD (n = 54) and walking-speed-matched control subjects (n = 39). Results: Statistical parametric mapping did not yield significant differences between PD and control groups for the vertical ground reaction force signal along the walking stance phase. Stride time and single support time (equivalent to swing time) were shorter and peak vertical ground reaction force was larger in PD patients compared to controls (p≤ 0.05). However, the single support time was no longer different between people with PD and healthy subjects when expressed relatively to stride time (p = 0.07). While single support, double support, and stance times were significantly more variable and asymmetric for PD than for the control group (p≤ 0.05), stride time was similar (p≥ 0.07). Discussion: These results indicate that at matched SSWS, PD patients adopt a higher cadence than control participants. Moreover, the temporal subdivision of the walking gait of people with PD is similar to healthy individuals but the coordination during the double support phase is different. Hence, this study indicates that isolating the speed factor is crucial in gait analysis for PD. [ABSTRACT FROM AUTHOR]

IntroductionParkinson’s disease (PD) is characterized by an alteration of the walking gait, frequently including a slower self-selected walking speed (SSWS). Although the reduction of walking speed is inherent to people with PD, such speed reduction also represents a potential confounding factor that might partly explain the observed gait differences between PD and control participants.MethodsIn this study, each participant walked along a 25 m level corridor during which vertical ground reaction force signals were recorded using shoes equipped with eight pressure sensors. Vertical ground reaction force signals (using statistical parametric mapping) and temporal and kinetic variables as well as their related variability and asymmetry (using Student’s t-test) were compared between PD (n = 54) and walking-speed-matched control subjects (n = 39).ResultsStatistical parametric mapping did not yield significant differences between PD and control groups for the vertical ground reaction force signal along the walking stance phase. Stride time and single support time (equivalent to swing time) were shorter and peak vertical ground reaction force was larger in PD patients compared to controls (p ≤ 0.05). However, the single support time was no longer different between people with PD and healthy subjects when expressed relatively to stride time (p = 0.07). While single support, double support, and stance times were significantly more variable and asymmetric for PD than for the control group (p ≤ 0.05), stride time was similar (p ≥ 0.07).DiscussionThese results indicate that at matched SSWS, PD patients adopt a higher cadence than control participants. Moreover, the temporal subdivision of the walking gait of people with PD is similar to healthy individuals but the coordination during the double support phase is different. Hence, this study indicates that isolating the speed factor is crucial in gait analysis for PD.

Objective: In this research, a marker-less ‘smart hallway’ is proposed where stride parameters are computed as a person walks through an institutional hallway. Stride analysis is a viable tool for identifying mobility changes, classifying abnormal gait, estimating fall risk, monitoring progression of rehabilitation programs, and indicating progression of nervous system related disorders. Methods: Smart hallway was build using multiple Intel RealSense D415 depth cameras. A novel algorithm was developed to track a human foot using combined point cloud data obtained from the smart hallway. A method was implemented to separate the left and right leg point cloud data, then find the average foot dimensions. Foot tracking was achieved by fitting a box with average foot dimensions to the foot, with the box’s base on the foot’s bottom plane. A smart hallway with this novel foot tracking algorithm was tested with 22 able-bodied volunteers by comparing marker-less system stride parameters with Vicon motion analysis output. Results: With smart hallway frame rate at approximately 60fps, temporal stride parameter absolute mean differences were less than 30ms. Random noise around the foot’s point cloud was observed, especially during foot strike phases. This caused errors in medial-lateral axis dependent parameters such as step width and foot angle. Anterior-posterior dependent (stride length, step length) absolute mean differences were less than 25mm. Conclusion: This novel marker-less smart hallway approach delivered promising results for stride analysis with small errors for temporal stride parameters, anterior-posterior stride parameters, and reasonable errors for medial-lateral spatial parameters.

Stride length analysis represents an easy method for assessing race walking kinematics. However, the stride parameters emerging from such an analysis have never been used to design a training protocol aimed at increasing stride length. With this aim, we investigated the effects of stride frequency manipulation during three weeks of uphill (2%) training on stride length at iso-efficiency speed. Twelve male race walkers were randomly allocated to one of two training groups: stride frequency manipulation (RWM, n=6) and free stride frequency (RWF, n=6). Results. Kinematic parameters measured before and after the 3-week training in RWM showed increased stride length (4.54%; p

Stride length analysis represents an easy method for assessing race walking kinematics. However, the stride parameters emerging from such an analysis have never been used to design a training protocol aimed at increasing stride length. With this aim, we investigated the effects of stride frequency manipulation during three weeks of uphill (2%) training on stride length at iso-efficiency speed. Twelve male race walkers were randomly allocated to one of two training groups: stride frequency manipulation (RWM, n=6) and free stride frequency (RWF, n=6). Results. Kinematic parameters measured before and after the 3-week training in RWM showed increased stride length (4.54%; p<0.0001) and contact time (4.58%; p<0.001); inversely, a decreased stride frequency (4.44%; p<0.0001) and internal work (7.09%; p<0.05) were found. In RWF the effect of the training showed a decrease in stride length (1.18%; p<0.0001) and contact time (<1%; p<0.0001) with respect to baseline conditions and an increased stride frequency and internal work of 1.19% (p<0.0001). These results suggest that using slopes (2%) as RWM could help coaches to provide some training methods that would improve an athlete’s performance, through increasing stride length without altering his or her race walking technique or metabolic demands. [ABSTRACT FROM AUTHOR]

The article discusses a study which investigated the reliability of the IR40, a new infrared light based method, in recording temporal stride patterns during treadmill running. The reason for the study is cited, along with the method and process employed for its implementation. Comparison results of the IR40 with contact shoe (CS) data recordings are explained. Comparative data is shown to support the conclusion that using the IR40 is plausible.

Abstract: Minimally invasive hip arthroplasty is thought to result in less soft tissue damage, earlier ambulation, and improved rehabilitation. This prospective blinded cohort study objectively analyzed early functional walking ability by stride analysis 2 days postoperatively. Ninety-five patients were analyzed, 43 of who received the minimal incision and 52 the traditional incision. Patients, physiotherapists, and assessors were blinded to the incision used. Velocity, cadence, stride length, operated and nonoperated limb step-length, and the ratio of step length of the operated to nonoperated limbs were recorded. No significant differences in any of these variables were shown between the minimal-incision and traditional-incision groups. This study demonstrates no functional benefits of the minimally invasive incision over the standard one in terms of early walking ability. [Copyright &y& Elsevier]

Objective: In this research, a marker-less 'smart hallway' is proposed where stride parameters are computed as a person walks through an institutional hallway. Stride analysis is a viable tool for identifying mobility changes, classifying abnormal gait, estimating fall risk, monitoring progression of rehabilitation programs, and indicating progression of nervous system related disorders., Methods: Smart hallway was build using multiple Intel RealSense D415 depth cameras. A novel algorithm was developed to track a human foot using combined point cloud data obtained from the smart hallway. A method was implemented to separate the left and right leg point cloud data, then find the average foot dimensions. Foot tracking was achieved by fitting a box with average foot dimensions to the foot, with the box's base on the foot's bottom plane. A smart hallway with this novel foot tracking algorithm was tested with 22 able-bodied volunteers by comparing marker-less system stride parameters with Vicon motion analysis output., Results: With smart hallway frame rate at approximately 60fps, temporal stride parameter absolute mean differences were less than 30ms. Random noise around the foot's point cloud was observed, especially during foot strike phases. This caused errors in medial-lateral axis dependent parameters such as step width and foot angle. Anterior-posterior dependent (stride length, step length) absolute mean differences were less than 25mm., Conclusion: This novel marker-less smart hallway approach delivered promising results for stride analysis with small errors for temporal stride parameters, anterior-posterior stride parameters, and reasonable errors for medial-lateral spatial parameters.