Validity of the microsoft kinect system in assessment of compensatory stepping behavior during standing and treadmill walking

Abstract Background Balance control, and specifically balance reactive responses that contribute to maintaining balance when balance is lost unexpectedly, is impaired in older people. This leads to an increased fall risk and injurious falls. Improving balance reactive responses is one of the goals in fall-prevention training programs. Perturbation training during standing or treadmill walking that specifically challenges the balance reactive responses has shown very promising results; however, only older people who are able to perform treadmill walking can participate in these training regimes. Thus, we aimed to develop, build, and pilot a mechatronic Perturbation Stationary Bicycle Robotic system (i.e., PerStBiRo) that can challenge balance while sitting on a stationary bicycle, with the aim of improving balance proactive and reactive control. Methods This paper describes the development, and building of the PerStBiRo using stationary bicycles. In addition, we conducted a pilot randomized control trial (RCT) with 13 older people who were allocated to PerStBiRo training (N = 7) versus a control group, riding stationary bicycles (N = 6). The Postural Sway Test, Berg Balance Test (BBS), and 6-min Walk Test were measured before and after 3 months i.e., 20 training sessions. Results The PerStBiRo System provides programmed controlled unannounced lateral balance perturbations during stationary bicycling. Its software is able to identify a trainee’s proactive and reactive balance responses using the Microsoft Kinect™ system. After a perturbation, when identifying a trainee’s trunk and arm reactive balance response, the software controls the motor of the PerStBiRo system to stop the perturbation. The pilot RCT shows that, older people who participated in the PerStBiRo training significantly improved the BBS (54 to 56, p = 0.026) and Postural Sway velocity (20.3 m/s to 18.3 m/s, p = 0.018), while control group subject did not (51.0 vs. 50.5, p = 0.581 and 15 m/s vs. 13.8 m/s, p = 0.893, respectively), 6MWT tended to improve in both groups. Conclusions Our participants were able to perform correct balance proactive and reactive responses, indicating that older people are able to learn balance trunk and arm reactive responses during stationary bicycling. The pilot study shows that these improvements in balance proactive and reactive responses are generalized to performance-based measures of balance (BBS and Postural Sway measures).

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Effect of Multisession Progressive Gait-Slip Training on Fall-Resisting Skills of People with Chronic Stroke: Examining Motor Adaptation in Reactive Stability

Brain Sciences ◽

10.3390/brainsci11070894 ◽

2021 ◽

Vol 11 (7) ◽

pp. 894

Author(s):

Shamali Dusane ◽

Tanvi Bhatt

Keyword(s):

Postural Stability ◽

Walking Speed ◽

Balance Control ◽

Center Of Mass ◽

Chronic Stroke ◽

Treadmill Walking ◽

Compensatory Stepping ◽

Lift Off ◽

Clinical Measures ◽

Reactive Balance

Background: This study examined whether a multisession gait-slip training could enhance reactive balance control and fall-resisting skills of people with chronic stroke (PwCS). Methods: A total of 11 PwCS underwent a four-week treadmill-based gait-slip training (four sessions). Pre- and post-training assessment was performed on six intensities of gait-slips (levels 1–6). Training consisted of 10 blocks of each progressively increasing intensity (four trials per block) until participants fell at >2 trials per block (fall threshold). In the next session, training began at a sub-fall threshold and progressed further. Fall outcome and threshold, number of compensatory steps, multiple stepping threshold, progression to higher intensities, pre- and post-slip center of mass (CoM), state stability, clinical measures, and treadmill walking speed were analyzed. Results: Post-training, PwCS demonstrated a reduction in falls and compensatory steps on levels 5 and 6 (p < 0.05) compared to pre-training. While an increase in pre-slip stability was limited to level 6 (p < 0.05), improvement in post-slip stability at lift-off was noted on levels 2, 3, and 5 (p < 0.05) along with improved post-slip minimum stability on levels 5 and 6 (p < 0.05). Post-training demonstrated improved fall (p < 0.05) and multiple stepping thresholds (p = 0.05). While most participants could progress to level 4 between the first and last training sessions, more participants progressed to level 6 (p < 0.05). Participants’ treadmill walking speed increased (p < 0.05); however, clinical measures remained unchanged (p > 0.05). Conclusions: Multisession, progressively increasing intensity of treadmill-based gait-slip training appears to induce significant adaptive improvement in falls, compensatory stepping, and postural stability among PwCS.

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The effects of mindfulness and music on affective responses to self-paced treadmill walking.

Sport Exercise and Performance Psychology ◽

10.1037/spy0000192 ◽

2020 ◽

Vol 9 (4) ◽

pp. 571-584

Author(s):

Anne E. Cox ◽

Sarah Ullrich-French ◽

Elaine A. Hargreaves ◽

Amanda K. McMahon

Keyword(s):

Affective Responses ◽

Treadmill Walking

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ADRENOCORTICAL RESPONSE TO NON-EXHAUSTIVE MUSCULAR EXERCISE

Acta Endocrinologica ◽

10.1530/acta.0.0700073 ◽

1972 ◽

Vol 70 (1) ◽

pp. 73-80 ◽

Cited By ~ 6

Author(s):

L. W. Raymond ◽

J. Sode ◽

J. R. Tucci

Keyword(s):

Treadmill Exercise ◽

Serum Cortisol ◽

Treadmill Walking ◽

Exhaustive Exercise ◽

Muscular Exercise ◽

Adrenocortical Response ◽

Exercise Tachycardia ◽

Before And After

ABSTRACT Treadmill walking produced a prompt reduction in serum cortisol in 10 of 12 healthy military men. In contrast, two subjects, with pre-exercise tachycardia and apprehension, showed an increase in serum cortisol with treadmill exercise. In each group, the changes produced by exercise were still evident 30 and 60 minutes after the 30-minute treadmill walk. Urine collected before and after exercise contained similar amounts of 11-hydroxy- and 17-hydroxycorticosteroid material. These results may be explained by an increase in cortisol utilization during exercise and/or by a change in its distribution. The data indicate that in the absence of psychic factors, non-exhaustive exercise is not associated with pituitary adrenocortical activation.

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THE EFFECTS OF TREADMILL WALKING COMBINED WITH OBSTALCE-CROSSING ON WALKING ABILITY IN AMBULATORY PATIENTS AFTER STROKE: A PILOT RANDOMIZED CONTROLLED TRIAL

10.26226/morressier.58e389add462b802923854b6 ◽

2017 ◽

Author(s):

Jung-Wan Koo

Keyword(s):

Randomized Controlled Trial ◽

Controlled Trial ◽

Treadmill Walking ◽

Walking Ability ◽

Randomized Controlled ◽

Ambulatory Patients ◽

Pilot Randomized Controlled Trial

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Arabic Dynamic Gestures Recognition Using Microsoft Kinect

Scientific Visualization ◽

10.26583/sv.10.5.09 ◽

2018 ◽

Vol 10 (5) ◽

pp. 140-159

Author(s):

B. Hisham ◽

A. Hamouda

Keyword(s):

Microsoft Kinect ◽

Dynamic Gestures

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3D Object Recognition and Relative Localization using a 3D sensor Embedded on a Mobile Robot

10.31237/osf.io/p4thn ◽

2020 ◽

Author(s):

Gopi Krishna Erabati

Keyword(s):

Pose Estimation ◽

Autonomous Systems ◽

Microsoft Kinect ◽

Object Localization ◽

Initial Alignment ◽

Relative Localization ◽

3D Data ◽

Industry Automation ◽

Ofthe Object ◽

3D Descriptors

The technology in current research scenario is marching towards automation forhigher productivity with accurate and precise product development. Vision andRobotics are domains which work to create autonomous systems and are the keytechnology in quest for mass productivity. The automation in an industry canbe achieved by detecting interactive objects and estimating the pose to manipulatethem. Therefore the object localization ( i.e., pose) includes position andorientation of object, has profound ?significance. The application of object poseestimation varies from industry automation to entertainment industry and fromhealth care to surveillance. The objective of pose estimation of objects is verysigni?cant in many cases, like in order for the robots to manipulate the objects,for accurate rendering of Augmented Reality (AR) among others.This thesis tries to solve the issue of object pose estimation using 3D dataof scene acquired from 3D sensors (e.g. Kinect, Orbec Astra Pro among others).The 3D data has an advantage of independence from object texture and invarianceto illumination. The proposal is divided into two phases : An o?ine phasewhere the 3D model template of the object ( for estimation of pose) is built usingIterative Closest Point (ICP) algorithm. And an online phase where the pose ofthe object is estimated by aligning the scene to the model using ICP, providedwith an initial alignment using 3D descriptors (like Fast Point Feature Transform(FPFH)).The approach we develop is to be integrated on two di?erent platforms :1)Humanoid robot `Pyrene' which has Orbec Astra Pro 3D sensor for data acquisition,and 2)Unmanned Aerial Vehicle (UAV) which has Intel Realsense Euclidon it. The datasets of objects (like electric drill, brick, a small cylinder, cake box)are acquired using Microsoft Kinect, Orbec Astra Pro and Intel RealSense Euclidsensors to test the performance of this technique. The objects which are used totest this approach are the ones which are used by robot. This technique is testedin two scenarios, fi?rstly, when the object is on the table and secondly when theobject is held in hand by a person. The range of objects from the sensor is 0.6to 1.6m. This technique could handle occlusions of the object by hand (when wehold the object), as ICP can work even if partial object is visible in the scene.

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