Ride quality meter

A ride quality meter is disclosed that automatically transforms vibration and noise measurements into a single number index of passenger discomfort. The noise measurements are converted into a noise discomfort value. The vibrations are converted into single axis discomfort values which are then converted into a combined axis discomfort value. The combined axis discomfort value is corrected for time duration and then summed with the noise discomfort value to obtain a total discomfort value

Vibration simulator studies for the development of passenger ride comfort criteria

A test program to determine the total discomfort associated with vehicle vibration is described. The program utilizes a three-degree-of-freedom vibration simulator to determine the effects of multifrequency and multiaxis vibration inputs. The approach to multifrequency vibration includes a separate consideration of the discomfort associated with each frequency component or band of the total spectrum and a subsequent empirical weighting of the discomfort components of these frequency bands when in various random combinations. The results are in the form of equal discomfort curves that specify the discomfort associated with discrete frequencies between 1 and 30 Hz and different acceleration levels. These results provide detailed information of the human discomfort response to increases in acceleration level for each frequency investigated. More importantly, the results provide a method for adding the discomfort associated with separate frequencies to give a total typification of the discomfort of a random spectrum of vibration

Combined Effects of Long-Term Sitting and Whole-Body Vibration on Discomfort Onset for Vehicle Occupants

Occupants of automobiles experience discomfort after long drives, irrespective of how well designed a seat might be. Previous studies of discomfort during driving have focused either on the seat shape and materials (“static” properties), long-term discomfort (“fatigue” properties), or dynamics (“vibration” properties). These factors have previously not been considered together. This paper reports three studies with objectives to define and test a model for describing long-term discomfort from vibration. Study 1 was an independent measures laboratory trial using an automobile seat, which lasted 80 minutes; Study 2 was a repeated measures laboratory trial using a rail passenger seat, which lasted 60 minutes; Study 3 was a repeated measures field trial in a people carrier automobile, which involved 70 minutes of travelling. The findings showed that discomfort accrues with time but that more discomfort is experienced when subjects are also exposed to whole-body vibration. Exposure to whole-body vibration accelerates development of discomfort. The relationship between the reported discomfort, the vibration magnitude, and the exposure time can be described using a multifactorial linear model. It is concluded that ignoring parts of the multi-factorial model (i.e., static, dynamic, or temporal factors) will compromise understanding of discomfort in context

Self-Reported Upper Body Discomfort due to Driving: Effect of Driving Experience, Gender and Automobile Age

This study investigated the human upper body discomfort caused by automobile driving. Both global and local discomfort estimates were achieved by means of a self-administered questionnaire. The questionnaire used a Borg CR10 scale to evaluate human discomfort, and contained sections to gather information regarding the driving experience, gender and most frequently used automobile of the respondent. The geographic area surveyed was the city of Turin, Italy, and data from a total of 269 drivers was analysed. For all subgroups analysed, the back region was reported to suffer the greatest discomfort, followed in order of decreasing discomfort by the neck, shoulder, arm, hand-wrist, forearm, head, chest and mandible. Generally, female drivers provided higher discomfort responses than male drivers. Subdividing the data according to driving experience lead to large and statistically significant (a<0.05) differences inboth global and local discomfort. Subdividing by gender suggested some significant differences, while subdividing by automobile age produced few differences. The results suggest the usefulness of controlling for test subject driving experience and gender when performing subjective evaluations of automobiles. Further, comparison of the global and the local discomfort responses suggested that individuals were able to form a stable estimate of global discomfort based on the sensations perceived in each of the individual body regions involved. This suggests the interesting possibility that global evaluations may not always provide an accurate understanding of human discomfort since situations can be imagined in which different distributions of upper body discomfort might produce the same, global, response

Diagnostic Prediction Using Discomfort Drawings with IBTM

In this paper, we explore the possibility to apply machine learning to make diagnostic predictions using discomfort drawings. A discomfort drawing is an intuitive way for patients to express discomfort and pain related symptoms. These drawings have proven to be an effective method to collect patient data and make diagnostic decisions in real-life practice. A dataset from real-world patient cases is collected for which medical experts provide diagnostic labels. Next, we use a factorized multimodal topic model, Inter-Battery Topic Model (IBTM), to train a system that can make diagnostic predictions given an unseen discomfort drawing. The number of output diagnostic labels is determined by using mean-shift clustering on the discomfort drawing. Experimental results show reasonable predictions of diagnostic labels given an unseen discomfort drawing. Additionally, we generate synthetic discomfort drawings with IBTM given a diagnostic label, which results in typical cases of symptoms. The positive result indicates a significant potential of machine learning to be used for parts of the pain diagnostic process and to be a decision support system for physicians and other health care personnel.Comment: Presented at 2016 Machine Learning and Healthcare Conference (MLHC 2016), Los Angeles, C

Initial subjective load carriage injury data collected by interviews and questionnaires

This study aimed to identify the types, incidence, and causes of any potential load carriage injuries or discomfort as a result of a 2-hour, forced-speed, treadmill march carrying 20 kg. Subjective load carriage data were collected, through both interviews and questionnaires, from relatively inexperienced soldiers after a period of load carriage. Results from the study showed that the upper limb is very susceptible to short-term discomfort, whereas the lower limb is not. The shoulders were rated significantly more uncomfortable then any other region, and blisters were experienced by ∼60% of participants. Shoulder discomfort commences almost as soon as the load is added and increases steadily with time; however, foot discomfort increases more rapidly once the discomfort materializes. In conclusion, early development of shoulder pain or blisters may be a risk factor for severe pain or noncompletion of a period of prolonged load carriage

An empirical analysis of potential cyclist injuries and cycling outfit comfort

This study investigated the relationship between pain/injury and training characteristics in cyclists. In addition, ergonomic wear comfort of their garments was investigated. A total of 94 complete questionnaire responses were analyzed. The result indicated that lower back pain was the most prevalent injury causing the highest rates of functional damage and medical attention. The injury level of cyclists was affected by the cluster with elite cyclists reporting pain while cycling. Many cyclists were not very satisfied with the comfort level of their current outfit, 39% of respondents were experienced with different discomfort sensations. The most frequent causes of discomfort were thermal and moisture discomfort sensation related to fabric characteristics. Moreover, design and fit of the garment were considered as cause of discomfort next to thermal discomfort sensation. Therefore, it could be concluded that garments that have good ventilation or breathability and very good fit values were preferred by cyclists. Design, limited choice (availability), appearance/look and quality were the main reason for their brand selection preferences

Discomfort luminance level of head-mounted displays depending on the adapting luminance

The Images in an immersive head-mounted display (HMD) for virtual reality provide the sole source for visual adaptation. Thus, significant, near-instantaneous increases in luminance while viewing an HMD can result in visual discomfort. Therefore, the current study investigated the luminance change necessary to induce this discomfort. Based on the psychophysical experiment data collected from 10 subjects, a prediction model was derived using four complex images and one neutral image, with four to six levels of average scene luminance. Result showed that maximum area luminance has a significant correlation with the discomfort luminance level than average, median, or maximum pixel luminance. According to the prediction model, the discomfort luminance level of a head-mounted display was represented as a positive linear function in log(10) units using the previous adaptation luminance when luminance is calculated as maximum area luminance