It was only a several decades ago that physiological measurements were recognized as effective indicators of human physical and mental conditions in occupational health or ergonomics. The recent rapid progress in sensor and signal processing techniques, however, made these available for practical evaluation techniques. This paper is an overview of the accumulated techniques in several fields including experimental psychology, physiology, medical sciences, and ergonomics. The major topics described herein are as follows: 1) properties and merits of physiological measurements compared with the other techniques, 2) applicability of various physiological indicators evaluated from noninvasive, ambulatory and continuous monitoring techniques, 3) practical physiological measurements and signal processing systems which can be applied at actual workplaces and environment, 4) effective and useful evaluation techniques of physiological indicators such as ECG, blood pressure, respiratory parameters, EEG, EBP, EMG, body movements, body temperature, perspiration, eye movements, CFF and electrodermal activities.
Our review of 235 published papers has shown that physiological measurements have made a significant contribution to the assessment of physical and mental workload, CNS (central nervous system) activity level and work performance. However, further studies should be mede on detail mechanisms and individual variations.

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To clarify workload factors in software developing work, we designed questionnaires composed of questions of work-content based on the interview survey. For the analysis of workload, Cumulative Fatigue Symptom Index (CFSI) and the stress-rating-method by 7-likert-scale were used. With the cooperation of the Japanese Software Engineers' Association (SEA) responses were obtained from 270 out of 1, 100 members and from 553 non-member software engineers in 18 companies in Japan.
The CFSI score obtained was higher than those of other groups of other industries obtained in our previous studies. The stress-rating showed that “time-pressure, ” “too much amount of work, and “ambiguity in job specification” were the highest stressors. The work groups were categorized by the results of CFSI profile into 4 types. The results of stress-ratings were significantly different between the 4 type groups. Based on the multiple comparison analysis, the workload factors of each group could be specified.
Out of the foregoing 4 types, the work groups which showed the deviation in F1B (depression) in CFSI and the work groups which showed high scores in every category in CFSI were higher in “ambiguity of specification” in stress-ratings. This result indicates that “ambiguity in specification” is a significant stressor in software engineers. This stressor is caused by the complicated communication process between users and engineers and by the shortage of tools or rules in this process. This stressor is considered to be the most typical workload which characterizes the software developing work.

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The aim of this study was to elucidate the time courses of amounts of urinary p-chloroaniline (p-CA) metabolites during acute poisoning and to establish a suitable method for biological monitoring of exposure to p-CA. Urinary p-CA metabolites which were previously identified in a patient with acute p-CA poisoning were determined quantitatively over time during admission of a patient by high-performance liquid chromatography (HPLC) and by the colorimetric method of diazo-positive metabolites (DPM). The data of urinary excretion of each p-CA metabolite were fitted to two-compartment model of pharmacokinetics.
Major urinary metabolites of p-CA were conjugated p-CA and conjugated 2-amino-5-chlorophenol (2-A-5-CP), and the detected amounts of 2, 4-dichloroaniline (2, 4-DCA) and free p-CA were small. During the rapid phase for the disappearance of each metabolite, half lives of p-CA, 2-A-5-CP and 2, 4-DCA were 2.4, 1.7 and 1.7 h, respectively, and during the slow phase, they were 4.5, 3.3 and 3.8 h, respectively. Urinary p-CA occupied about 62% of the total metabolites detected in the urine, 2-A-5-CP about 36%, and 2, 4-DCA about 1%. 2-A-5-CP and p-CA were detected in the urine of the patient obtained on days 3 and 4, respectively, after the poisoning, but the amount of DPM after the second day of the poisoning was in the ranged of that of non-exposed persons.
As the colorimetric method was not accurate for biological monitoring at a low level exposure of p-CA, measurement of urinary p-CA or 2-A-5-CP by HPLC is considered to be more suitable for biological monitoring of p-CA exposure.

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The Zung self-rating depression scale (SDS) was applied to Japanese night shift workers of a railway company in order to assess the prevalence of depressive state and clarify the structural characteristics of the SDS questionnaire.
Out of 2, 394 employees, 1, 931 male workers were engaged in night shift work and 1, 274 men (66.0%) completely answered the questionnaire. The control group was selected from daytime workers.
The average age of the subjects was 39.4. Cronbach's alpha coefficient of the night shift workers was 0.835 and that of the control was 0.848. SDS index decreased with age. The mild, moderate, and severe depressive state of night shift workers evaluated by SDS were 13.7%, 2.1%, and 0.6%, respectively. A two-way analysis of variance on SDS index examined age and shift work. Age influenced SDS index, but there was no interaction between the factors. Two factors were extracted by factor analysis. Factor 1 consisted of 8 positive items, accounting for 16.7%. Factor 2 consisted of 8 depressive items, accounting for 15.6%. The residual four items consisted of somatic or behavioral features. Mean value of SDS index by age, distribution of SDS index, and factor structure of SDS questions of the night shift workers were similar to those of the control group.

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A questionaire survey on periodic health checkup was conducted on 4, 432 manufacturing factories in Kawasaki and the following results were obtained.
1) Implementation rate of periodic health checkup was 100% in factories with 100 workers or more. In smaller factories employing less than 100 workers, the implementation rate decreased with decrease in their total work force. The rate was 47.5% and 37.7% in factories with 9-4 and 3-1 workers, respectively.
2) The proportion of workers less than 30 years of age decreased and that of 60 or more years of age increased with decreasing size of the total work force. Distribution of both age groups was 12.6% and 12.9%, respectively in factories with less than 10 workers. The proportion of female workers increased from about 10% in factories with 300 workers or more to 26.8% in factories with less than 10 workers.
3) In large factories with 500 workers or more periodic health checkups were implemented mostly at their own or related medical facilities and in factories with 499-10 workers, almost 50% were implemented in independent health service facilities. In factories with less than 10 workers periodic health checkup were implemented mainly at health centers (33.1%) and at hospitals or clinics (26.9%).
4) The main reasons why small factories could not implement periodic health checkup were: (1) they could not afford the time for the implementation (50.0%) and (2) ignorance of the law of mandatory periodic health checkup for workers (23.6%).

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