Patients underwent clinical gait analysis before (PRE), 1 month (T1), and 3 months after (T3) surgery in the Motion Analysis Laboratory of our institute. For the gait analysis, a Helen Hayes marker set of 22 retro-reflective passive markers was used and a Davis biomechanical model was applied during data acquisition and processing (Davis et al. 1991 ). Patients were asked to walk as best as they could at a self-selected speed without walking aids along a 13-meter walkway at least 6 times. An optoelectronic system (SMART-D, BTS Bioengineering, Milan, Italy) with 8 infrared cameras (sampling rate 100 Hz) was used for spatiotemporal and kinematic data acquisition. Mark trajectories were recorded, reconstructed, and processed by SMART-D Analyzer software (BTS Bioengineering, Quincy, MA, USA). The gait parameters were: (1) spatiotemporal variables: stance phase (percentage), swing phase (percentage) step length (meters), stride length (meters), gait speed (m/s), and gait cadence (steps/minute); stance and swing were normalized as a percentage of the gait cycle; (2) kinematic parameters (in degrees): hip flexion–extension ROM, hip abduction–adduction ROM, hip rotation ROM, hip obliquity ROM.
Smart d
Manufactured by BTS Bioengineering
Sourced in Italy
The Smart-D is a compact and versatile laboratory equipment designed for precise temperature and humidity control. It features a user-friendly digital interface and advanced sensors to maintain optimal environmental conditions for various experiments and applications.
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Lab products found in correlation
7 protocols using smart d
1
Gait Analysis of Surgical Patients
2
Gait Analysis in Rehabilitation Patients
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For gait analysis, a Helen Hayes marker set of 22 retro-reflective passive markers was used and a Davis biomechanical model was utilized during data acquisition and processing39 . Patients were asked to walk at a self-paced speed with a walking aid along a 13-meter walkway five times. An optoelectronic system (SMART-D, BTS Bioengineering, Milan, Italy) with eight infrared cameras (sampling rate 100 Hz) was used for spatiotemporal and kinematic data acquisition during each walking section. Marker trajectories were recorded, reconstructed, and processed by SMART-D Analyzer software (BTS Bioengineering). The gait parameters collected were: (i) spatiotemporal variables — stride length (m), gait speed (m/s), gait cadence (steps/min), stance phase, swing phase, and double support phase; stance, swing and double support phases were normalized as a percentage of the gait cycle and (ii) kinematic parameters (in degrees): knee range of motion (ROM). These measures were collected in 36 patients (18 patients of the experimental group and 18 patients of the control group).
3
Webcam-Based Gait Analysis System
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Two full-HD webcams (PC-W1, Aukey, Shenzhen, China) with a native image resolution of 1920 × 1080 pixels and a 1/2.7” CMOS sensor were used. Cameras acquired images at 30 Hz, with contrast and brightness automatically selected by the software provided by the manufacturer. Cameras were fastened on an aluminum bar perpendicular to the strait gait direction at a height of 2.3 m, framing the subject frontally.
A stereophotogrammetric motion analyser (Smart-D, BTS Bioengineering, Milano, Italy) equipped with eight infrared cameras sampling at 100 Hz was used as reference measurement system. The system was calibrated according to the manufacturer's specification, and the error in markers' location reconstruction was 0.2 mm on a working volume of 3 × 2 × 2 m.Figure 1 shows the implemented measurement infrastructure.
A stereophotogrammetric motion analyser (Smart-D, BTS Bioengineering, Milano, Italy) equipped with eight infrared cameras sampling at 100 Hz was used as reference measurement system. The system was calibrated according to the manufacturer's specification, and the error in markers' location reconstruction was 0.2 mm on a working volume of 3 × 2 × 2 m.
4
Gait Kinematics and Kinetics Assessments
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The acquisitions of HYA's kinematic and kinetic data were performed at BioMovLab (Department of Information Engineering, University of Padova, Italy). A 6-cameras optoelectronic system (Smart E, 60-120 Hz, BTS Bioengineering S.p.A., Garbagnate Milanese (MI), Italy) captured the three-dimensional trajectories (frame rate = 60 Hz) according to the modified IOR-gait protocol as in (Sawacha et ). A force plate (FP4060, 960 Hz, Bertec Corporation, Columbus, Ohio, Canada) synchronously acquired the CoP displacement while the Romberg test was performed. The acquisitions of PPD's kinematic and kinetic data were performed at the Rehabilitation Facility, GVDR, Padova, Italy, throughout an 8-cameras optoelectronic system (Smart D, 300 Hz, BTS Bioengineering S.p.A., Garbagnate Milanese (MI), Italy) and a synchronized force plate (BTS-p-6000, 1200 Hz, BTS Bioengineering S.p.A., Garbagnate Milanese (MI), Italy). The same marker set as the one adopted for the YHA was applied. Moreover, the same examiner used the same system and the same Matlab (version R2021b, MathWorks, USA) was adopted for the data processing.
5
Chest Wall Motion Capture Protocol
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A motion capture system (Smart-D, BTS Bioengineering Corp., Milan, Italy), hereinafter referred to as a mocap, was used as a reference device for detecting chest wall displacements and compartmental breathing volumes. To calculate the breathing volumes from chest wall displacements, a chest wall model must be developed. Different marker protocols have been used in previous studies based on 89, 86, 32 and 30 markers. The 89 marker model seems to allow a more accurate reconstruction of the chest wall surface and is therefore considered the gold standard. However, the high number of markers required can affect the reproducibility of measurements, and markers placing, data collection, and post-processing of the marker data can be challenging and time-consuming [43 (link)]. Recently, the 32 marker protocol reported in [44 (link)] has been demonstrated to be sufficiently accurate to determine rib cage and abdomen compartmental volumes and thoraco-abdominal motion pattern (in terms of compartmental percentage contributions, and coordination between compartments). In this paper we adopted a 40 marker protocol to better differentiate the left and right side of the chest wall needed for the specific application (hemilateral kinematics assessment). The 40 markers are positioned according to Figure 2 and the chest wall Rc and AB compartments are shown in Figure 3 .
6
Overground Gait Analysis using MoCap
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A MoCap was used as the reference system for the overground gait analysis. Eight infrared cameras of the MoCap (SMART D by BTS Bioengineering, Milan, Italy) were positioned around the treadmill (Figure 1 ). Trajectories of retro-reflective passive markers were recorded at 60 Hz. The inter-laboratory reliability of this system was demonstrated by Benedetti et al. [34 (link)].
7
Kinematic Analysis of Gait Mechanics
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A N U S C R I P T 6 gait kinematics were analyzed using an optoelectronic eight-camera system (120 Hz; Smart-D, BTS Bioengineering, Italy). After instrumentation, participants practiced walking forwards at their preferred speed over a 10 m platform, then completed six trials of gait with 30 s of rest between trials. Participants self-initiated their gait for each trial. Marker position data and EMG data from forward, straight-walking and constant-speed strides of each leg were subsequently analyzed.
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