Simon Choppin

Development and assessment of a Microsoft Kinect based system for imaging the breast in three dimensions

Three-dimensional surface imaging technologies have been used in the planning and evaluation of breast reconstructive and cosmetic surgery. The aim of this study was to develop a 3D surface imaging system based on the Microsoft Kinect and assess the accuracy and repeatability with which the system could image the breast. A system comprising two Kinects, calibrated to provide a complete 3D image of the mannequin was developed. Digital measurements of Euclidean and surface distances between landmarks showed acceptable agreement with manual measurements. The mean differences for Euclidean and surface distances were 1.9mm and 2.2mm, respectively. The system also demonstrated good intra- and inter-rater reliability (ICCs>0.999). The Kinect-based 3D surface imaging system offers a low-cost, readily accessible alternative to more expensive, commercially available systems, which have had limited clinical use.

The potential of the Microsoft Kinect in sports analysis and biomechanics

The objective of this study was to assess the suitability of the Microsoft Kinect depth camera as a tool in segment scanning, segment tracking and player tracking. A mannequin was scanned with the Kinect and a laser scanner. The geometries were truncated to create torso ‘segments’ and compared. Separate shoulder abduction ( − 100° to 50°) and flexion motions (0°–100°) were recorded by the Kinect (using free and commercial software) and a Motion Analysis Corporation (MAC) system. Segment angles were compared. A participants centre of mass (COM) was tracked over a 6 × 3 m floor area using the Kinect and a MAC system and compared. Mean errors with uncertainty of the mass, COM position and principal moments of inertia were − 1.9 ± 1.6%, 0.5 ± 0.4% and 3 ± 2.6%, respectively. The commercial software gave the highest accuracy, in which the maximum and root mean square errors (RMSEs) were 13.85° and 7.59° in abduction and 21.57° and 12.00° in flexion. RMSEs in X, Y and Z COM positions were 0.12, 0.14 and 0.08 m, respectively, although vertical position (Y) was subject to a large systematic bias of 405 mm. The Kinects low cost and depth camera are an advantage for sports biomechanics and motion analysis. Although segment tracking accuracy is low, the Kinect could potentially be used in coaching and education for all three application areas in this study.

Calculating Body Segment Inertia Parameters from a Single Rapid Scan Using the Microsoft Kinect

Many biomechanical analyses rely on the availability of reliable body segment inertia parameter (BSIP) estimates. Current processes to obtain these estimates involve many time consuming manual measurements of the human body, used in conjunction with models or equations. While such methods have become the accepted standard they contain many inherent errors arising from manual measurement and significant assumptions made in the underlying data used to form the models and equations. Presented here is an alternative approach to obtaining reliable estimates of body segment inertia parameters through the use of the Microsoft Kinect sensor. A 3D scanning system was developed, comprising four Kinects aligned to a single global coordinate system using rigid body calibration and random sample consensus (RANSAC) optimisation. The system offers the advantage of obtaining BSIP estimates in a single scanning operation of around three seconds, much quicker than the circa thirty minutes of manual measurements required for existing BSIP estimate methods. The results obtained with the system show a mean error of 0.04% and a standard deviation of 2.11% in volumetric measurements of a torso manikin, suggesting comparable and in many cases, greater accuracy volumetric estimates than a commonly used geometric BSIP model. Further work is needed to extend this study to include a full range of BSIP measurements across more of the bodies segments and to include scanning of living human subjects. However, this initial study suggests great potential for a low cost system that can provide quick and accurate subject BSIP estimates.

Assessing the suitability of the Microsoft Kinect for calculating person specific body segment parameters

Many biomechanical and medical analyses rely on the availability of reliable body segment parameter estimates. Current techniques typically take many manual measurements of the human body, in conjunction with geometric models or regression equations. However, such techniques are often criticised. 3D scanning offers many advantages, but current systems are prohibitively complex and costly. The recent interest in natural user interaction (NUI) has led to the development of low cost (~£200) sensors capable of 3D body scanning, however, there has been little consideration of their validity. A scanning system comprising four Microsoft Kinect sensors (a typical NUI sensor) was used to scan twelve living male participants three times. Volume estimates from the system were compared to those from a geometric modelling technique. Results demonstrated high reliability (ICC>0.7, TEM<1 %) and presence of a systematic measurement offset (0.001m\(^{3}\)), suggesting the system would be well received by healthcare and sports communities.

Assessment of a Microsoft Kinect-based 3D scanning system for taking body segment girth measurements: a comparison to ISAK and ISO standards

ABSTRACT Use of anthropometric data to infer sporting performance is increasing in popularity, particularly within elite sport programmes. Measurement typically follows standards set by the International Society for the Advancement of Kinanthropometry (ISAK). However, such techniques are time consuming, which reduces their practicality. Schranz et al. recently suggested 3D body scanners could replace current measurement techniques; however, current systems are costly. Recent interest in natural user interaction has led to a range of low-cost depth cameras capable of producing 3D body scans, from which anthropometrics can be calculated. A scanning system comprising 4 depth cameras was used to scan 4 cylinders, representative of the body segments. Girth measurements were calculated from the 3D scans and compared to gold standard measurements. Requirements of a Level 1 ISAK practitioner were met in all 4 cylinders, and ISO standards for scan-derived girth measurements were met in the 2 larger cylinders only. A fixed measurement bias was identified that could be corrected with a simple offset factor. Further work is required to determine comparable performance across a wider range of measurements performed upon living participants. Nevertheless, findings of the study suggest such a system offers many advantages over current techniques, having a range of potential applications.

The accuracy of the Microsoft Kinect in joint angle measurement

The Microsoft Kinect is a cheap consumer device capable of markerless body segment tracking. While it was not originally designed for research applications, studies have been performed which utilise its capabilities. In order to better define the suitability of the device in a clinical and biomechanical context, a study was performed which assessed the accuracy of the device in 12 separate movements and for two different software-based tracking algorithms (IPIsoft and NITE). The movements were chosen to represent a variety of joint motions and speeds. Ten participants (height, 185 ± 6 cm; mass, 77 ± 9 kg) performed each movement while the Kinect and a Motion Analysis Corporation capture system recorded simultaneously. The procedure was performed twice, once for each tracking algorithm. Median values for RMSE, maximum error, systematic bias and proportional bias were 12.6°, 58.2°, 4.38° and 1.15°, respectively, for the IPIsoft algorithm and 13.8°, 63.1°, 3.16° and 1.19°, respectively, for the NITE algorithm. While maximum errors are high the system has many advantages over existing multi-camera markerless tracking systems. The Kinect could be used in low speed analysis of simple human motions where cost and ecological validity are of high priority.

Ball and Racket Movements Recorded at the 2006 Wimbledon Qualifying Tournament (P109)

This paper contains the recorded shot movements of 13 players in practice conditions at the Wimbledon 2006 Qualifying Tournament. A 2-camera 3D system was used to track the racket and ball for a period of 0.02 seconds for each recorded shot. Custom-written analysis software was used to extract the required co-ordinates from the ball and racket positions and transform them into 3D. From this information the following things were obtained; ball velocity before and after impact; racket linear and angular velocity before impact; ball spin and impact position. It was found that although ball velocity was very similar for all players before impact, male players were able to generate higher ball velocities after impact. This was found to be due to a higher racket COM velocity. Impact position and angular velocities were very similar for both sexes.

Distortion correction of depth data from consumer depth cameras

Since the introduction of the Microsoft Kinect in November 2010, low cost consumer depth cameras have rapidly increased in popularity. Their integral technology provides a means of low cost 3D scanning, extending its accessibility to a far wider audience. Previous work has shown the 3D data from consumer depth cameras to exhibit fundamental measurement errors: likely due to their low cost and original intended application. A number of techniques to correct the errors are presented in the literature, but are typically device specific, or rely on specific open source drivers. Presented here is a simple method of calibrating consumer depth cameras, relying only on 3D scans of a plane filling the field of view: thereby compatible with any device capable of providing 3D point cloud data. Validation of the technique using a Microsoft Kinect sensor has shown non planarity errors to reduce to around ± 3mm: nearing the device’s resolution. Further validation based on circumference measures of a cylindrical object has shown a variable error of up to 45mm to reduce to a systematic overestimation of 10mm, based on a 113mm diameter cylinder. Further work is required to test the proposed method on objects of greater complexity and over greater distances. However, this initial work suggests great potential for a simple method of reducing the error apparent in the 3D data from consumer depth cameras: possibly increasing their suitability for a number of applications.

Validity and repeatability of a depth camera-based surface imaging system for thigh volume measurement

ABSTRACT Complex anthropometrics such as area and volume, can identify changes in body size and shape that are not detectable with traditional anthropometrics of lengths, breadths, skinfolds and girths. However, taking these complex with manual techniques (tape measurement and water displacement) is often unsuitable. Three-dimensional (3D) surface imaging systems are quick and accurate alternatives to manual techniques but their use is restricted by cost, complexity and limited access. We have developed a novel low-cost, accessible and portable 3D surface imaging system based on consumer depth cameras. The aim of this study was to determine the validity and repeatability of the system in the measurement of thigh volume. The thigh volumes of 36 participants were measured with the depth camera system and a high precision commercially available 3D surface imaging system (3dMD). The depth camera system used within this study is highly repeatable (technical error of measurement (TEM) of <1.0% intra-calibration and ~2.0% inter-calibration) but systematically overestimates (~6%) thigh volume when compared to the 3dMD system. This suggests poor agreement yet a close relationship, which once corrected can yield a usable thigh volume measurement.

Breast Volume Calculation Using a Low-Cost Scanning System

Breast volume has been identified as a key metric in assessing patients for reconstructive surgery. Scanning systems have measured breast volume but they have tended to rely on expensive hardware and software. This paper discusses the development and assessment of an algorithm capable of calculating breast volume from 3D point data. A mannequin was scanned (using a custom, Kinect based scanning system) with one of two breast prostheses attached – 400g or 600 g. Each scan was assessed by three independent operators: seven anatomical points were identified representing the boundary of the breast region, which was then isolated. A Coons patch was used to represent the invisible chest surface lying below the breast tissue. A trapezium rule based approach was used to calculate the volume of the enclosed region between the breast and chest surfaces. Breast volume over-estimated by 130 cc with the 400 g prosthesis (30.3%) and 206 cc (33.3%) with the 600 g prosthesis, suggesting positive proportional bias. Average reliability was ± 59.7 cc for the 400 g prosthesis (13.9%) and ± 34.7 cc for the 600 g prosthesis (5.6%) – approaching the levels required to differentiate between implant sizes (25 -50 cc). Future work will focus on refining the hardware and software of this scanning system – minimising proportional basis and maximising reliability of measurement.