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At least 19 recordsLinked to original sources
PubMed1981

A multivariate comparison between two EEG analysis techniques: period analysis and fast Fourier transform.

The present study investigated the statistical correspondence between two frequently used methods of analysing tonic EEG activity: (1) period analysis and (2) Fast Fourier Transforms (FFTs). For replication purposes, independent statistical analyses were carried out on the EEG of sleeping subjects and of awake subjects performing a cognitive task. From the results of two canonical correlations, the first two canonical variates were sufficient to account for 97% (awake group) and 99% (sleeping group) of the variance between the separate linear composites of all FFT and period analysis variables. Linear regressions of the 3 dependent measures generated by period analysis onto each respective FFT measure gave high and significant multiple correlations for all frequencies. Zero-order correlations were also gathered and discussed. It is concluded that period analytic and FFT analysed EEG share similar types of information and that period analysis can be used more often in EEG research.

Arousal↗
PubMed2004

Providing more up-to-date estimates of patient survival: a comparison of standard survival analysis with period analysis using life-table methods and proportional hazards models.

OBJECTIVE: Standard survival methods can yield out-of-date estimates of long-term survival. Period analysis, based on life-table methodology, provides more up-to-date survival estimates by exploring survival during a restricted recent period of interest. It excludes the short-term survival of patients recruited at the start of the study. We use statistical models to further develop the method of period analysis, providing more up-to-date estimates of survival and the ability to explore differences in survival by covariates and adjust for case mix. METHODS: We use cancer registry data for colorectal cancer in Leicestershire, UK, to illustrate the use of Cox proportional hazards (CPH) models to estimate period and standard survival. We compare these estimates with those obtained using life-table methodology. RESULTS: Period estimates were slightly higher than the standard estimates as they reflect recent improvements in short-term survival. The results for period analysis using the life-table approach and using CPH models were similar. However, CPH models allowed further investigation of other risk factors and the ability to control for potential confounding variables. CONCLUSION: Using period survival estimates, more up-to-date information is available to clinicians and others with an interest in monitoring survival. Period CHP models offer all the advantages of statistical modeling, and are straightforward to fit in standard statistical packages.

Colorectal Neoplasms↗
PubMed2002

Use of period analysis for providing more up-to-date estimates of long-term survival rates: empirical evaluation among 370,000 cancer patients in Finland.

BACKGROUND: Providing up-to-date estimates of cancer patient survival rates is an important task of cancer registries. A few years ago, a new method of survival analysis, denoted period analysis, was proposed to enhance the recency of long-term survival estimates. The aim of this paper is to provide a comprehensive empirical evaluation of the use of this method. METHODS: Using data from the nationwide Finnish Cancer Registry, we compare 5-year and 10-year relative survival rates of 371 849 patients diagnosed with one of the 16 most common forms of cancer in Finland at various time intervals between 1953 and 1992 with the most up-to-date estimates of 5-year or 10-year relative survival that might have been obtained in those time intervals by traditional methods of survival analysis and by period analysis of survival. RESULTS: Survival rates strongly increased over time for most forms of cancer. For these cancers, traditional estimates of 5- and 10-year survival rates would have severely lagged behind the survival rates later observed for newly diagnosed patients, and period analysis would consistently have provided much more up-to-date estimates of survival rates. CONCLUSIONS: We conclude that period analysis should be implemented as a standard tool for providing up-to-date estimates of long-term survival rates by cancer registries.

Aged↗
PubMed2002

Up-to-date long-term survival curves of patients with cancer by period analysis.

PURPOSE: Provision of up-to-date long-term survival curves is an important task of cancer registries. Traditionally, survival curves have been derived for cohorts of patients diagnosed many years ago. Using data of the Finnish Cancer Registry, we provide an empirical assessment of the use of a new method of survival analysis, denoted period analysis, for deriving more up-to-date survival curves. PATIENTS AND METHODS: We calculated 10-year relative survival curves actually observed for patients diagnosed with one of the 15 most common forms of cancer in 1983 to 1987, and we compared them with the most up-to-date 10-year relative survival curves that might have been obtained in 1983 to 1987 using either traditional (cohort-wise) or period analysis. We also give the most recent 10-year survival curves obtained by period analysis for the 1993 to 1997 period. RESULTS: For all forms of cancer, period analysis of the 1983 to 1987 data yielded survival curves that were very close to the survival curves later observed for patients who were newly diagnosed in that period (median and maximum difference of 10-year relative survival estimates: 0.9 and 5.7 percent units, respectively). By contrast, the survival curves obtained by traditional (cohort-wise) survival analysis in 1983 to 1987 would have been much lower for most forms of cancer (median and maximum difference: 5.8 and 18.4 percent units, respectively). The 10-year survival curves for the 1993 to 1997 period are substantially more favorable than previously available, traditionally derived survival curves for most forms of cancer. CONCLUSION: Period analysis is a useful tool for deriving up-to-date long-term survival curves of patients with cancer.

Humans↗
PubMed2003

Up-to-date survival curves of children with cancer by period analysis.

Survival rates of children with cancer have strongly improved during the past decades, but much of this improvement has been disclosed with substantial delay by traditional methods of survival analysis, which reflect survival experience of patients diagnosed many years ago. In this paper, the use of a new method of survival analysis, denoted period analysis, for providing more up-to-date estimates of 10-year survival curves of children with cancer is empirically evaluated using data of the Surveillance, Epidemiology, and End Results Program of the United States National Cancer Institute. It is shown that period analysis provides much more up-to-date estimates of survival curves than traditional cohort-based survival analysis indeed, at least as long as there is ongoing improvement in survival rates over time, as it seems to be the case for many forms of childhood cancer. The most recent 10-year period survival estimates indicate that survival rates of children with cancer achieved by the end of the 20th century are substantially higher than previously available survival statistics have suggested. Application of period analysis may be particularly useful in the field of childhood cancer as it may help to prevent patients, their families and clinicians from being burdened by outdated, often too pessimistic survival expectations.

Adolescent↗
PubMed2002

A computer program for period analysis of cancer patient survival.

Monitoring of long-term survival rates, which is now routinely performed by many cancer registries throughout the world, should be as up-to-date as possible. A few years ago, a new method of survival analysis, denoted period analysis, has been proposed which provides more up-to-date estimates of long-term survival rates than traditional survival analysis by exclusively reflecting the survival experience of patients within a recent calendar period. However, application of this method has so far been hindered by the lack of pertinent computer programs. In this paper, we present a simple and easy-to-use computer program (SAS macro) that enables one to carry out period analysis (as well as conventional analysis) of both absolute and relative survival rates with the type of data commonly available in population-based cancer registries. We illustrate application of the program with examples from the nationwide Finnish Cancer Registry.

Female↗
PubMed2004

Period analysis for 'up-to-date' cancer survival data: theory, empirical evaluation, computational realisation and applications.

Long-term survival rates are the most commonly used outcome measures for patients with cancer. However, traditional long-term survival statistics, which are derived by cohort-based types of analysis, essentially reflect the survival expectations of patients diagnosed many years ago. They are therefore often severely outdated at the time they become available. A couple of years ago, a new method of survival analysis, denoted period analysis, has been introduced to derive more 'up-to-date' estimates of long-term survival rates. We give a comprehensive review of the new methodology, its statistical background, empirical evaluation, computational realisation and applications. We conclude that period analysis is a powerful tool to provide more 'up-to-date' cancer survival rates. More widespread use by cancer registries should help to increase the use of cancer survival statistics for patients, clinicians, and public health authorities.

Cohort Studies↗
PubMed2002

Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis.

BACKGROUND: Long-term survival rates for many types of cancer have substantially improved in past decades because of advances in early detection and treatment. However, much of this improvement is only seen many years later with traditional cohort-based methods of survival analysis. I aimed to assess achievements in cancer patients' survival by an alternative method of survival analysis,known as period analysis, which provides more up-to-date estimates of long-term survival rates than do conventional methods. METHODS: The 1973-98 database of the Surveillance, Epidemiology, and End Results (SEER) programme of the US National Cancer Institute was analysed by period analysis. FINDINGS: Estimates of 5-year, 10-year, 15-year, and 20-year relative survival rates for all types of cancer were 63%, 57%, 53%, and 51%, respectively, by period analysis. These estimates were 1%, 7%, 11%, and 11% higher, respectively, than corresponding estimates by cohort-based survival analysis. By period analysis, 20-year relative survival rates were close to 90% for thyroid and testis cancer, exceeded 80% for melanomas and prostate cancer, were about 80% for endometrial cancer, and almost 70% for bladder cancer and Hodgkin's disease. A 20-year relative survival rate of 65% was estimated for breast cancer, of 60% for cervical cancer, and of about 50% for colorectal, ovarian, and renal cancer. INTERPRETATION: Timely detection of improvements in long-term survival rates might help to prevent clinicians and their patients from undue discouragement or depression by outdated and often overly pessimistic survival expectations. It also adds to the value of cancer surveillance as a basis for appropriate public-health decisions.

Cause of Death↗
PubMed1993

Digital period analysis of EEG in depression: periodicity, coherence, and interhemispheric relationships during sleep.

1. Interhemispheric EEG differences were compared between 12 symptomatic depressed outpatients, 12 asymptomatic patients and 12 normal controls during two consecutive nights in the Sleep Study Unit. 2. EEG was quantified using digital period analysis (DPA), a time-domain analysis of successive polarity changes (zero-cross) and instances of zero slope (first derivative), yielding percent-time in each frequency band. 3. The degree of hemispheric asymmetry (L-R) was computed for delta, beta and theta percentages from REM, Stage 2 and Slow-Wave (SW) sleep. 4. Normals showed small asymmetries throughout sleep with largest differences in SW, with no consistent relationship between right and left activity and sleep stage. 5. Both depressed groups showed largest asymmetries in REM sleep, with significantly more beta, theta and delta in the right hemisphere consistently. None of the 24 depressed patients showed greater left hemisphere activity throughout sleep.

Adult↗
PubMed2005

Period analysis of cancer patient survival in datasets from which the month of diagnosis has been removed.

Up-to-date monitoring of long-term survival is an important task of population-based cancer registries. Period analysis, a new method of survival analysis introduced a few years ago, has been shown to be particularly useful for that purpose. The "classical" period analysis uses a life-table approach which requires both the year and month of diagnosis for implementation in pertinent software programs. However, an increasing number of cancer registries remove the month of diagnosis from their datasets, mainly to ensure the highest possible protection against re-identification of patients. In this paper, we present modifications of period analysis that allow the application of this technique, while almost completely preserving its advantages, in datasets without the month of diagnosis. The modified techniques are illustrated and evaluated using examples from the Surveillance, Epidemiology, and End Results (SEER) programme of the United States (US) National Cancer Institute (NCI), which also has removed month of diagnosis from its most recently released public use database.

Adolescent↗
PubMedDate not supplied

[Sleep polygraphy: diagnostic value in depressive pseudo-dementia. Attempt to improve visual scoring by digital periodic analysis].

ARGUMENT: Pseudo depressive dementia is a common pathology for elderly patients. Classically, it is said that depression is taking the mask of dementia, but very often deterioration and depression are present at the same time. Sleep EEG can help the clinician to differentiate dementia and depression in pseudo depressive dementia. Slow Wave Sleep (SWS) is a good indicator of deterioration process. We tried to improve the sleep recording and analysis and our ability to differentiate SWS in this indication. We use a portable digital recording material (Hypnotrace). The signal is analysed by the association of a visual standard method to Digital Periodic Analysis (DPA) which is very sensitive to SWS. The visual analysis gives informations about the macroarchitecture of the night. The Digital Periodic Analysis gives at any moment the value of the wave frequency and thus informations about the microarchitecture. Our hypothesis is that this association helps to better recognise SWS and thus improves sleep EEG as a diagnostic tool in this indication. METHODS: 23 inpatients meeting both the criteria for major depression and dementia (DSM IV) have been recorded during two nights after 15 days of wash out and before antidepressant treatment. The recordings are analysed with the visual standard method and with the help of DPA. The patients are evaluated every 15 days during two months in order to define three groups based on the clinical evolution. RESULTS: The scoring with DPA is more sensitive to Slow Wave Sleep, particularly for the patients with good clinical evolution (with the strongest depressive component). Thus, this method could be a good diagnostic tool to differentiate dementia and depression in pseudo depressive dementia.

Aged↗
PubMed1991

Speech-related body movement in aphasia: period analysis of upper arms and head movement.

The effects of aphasia on coverbal body movement have important implications for the understanding of both normal and pathological speech processes. The related findings were often inconsistent, partly due to inherent methodological difficulties which could be reduced by the use of advanced techniques of movement monitoring (Hadar, 1991). The present study employed a new computerized system, CODA-3, which locates small prismatic markers and computes by triangulation their three-dimensional position at 100 Hz. Movement of the head and the upper arms was monitored in 15 aphasic and normal subjects engaged in speech during a naturalistic interview. Movement analysis was based on automatized identification of successive movement extrema ("period analysis") and the computation of amplitude, duration, and velocity of each period. The results showed higher incidence and amplitude of all body movement in the aphasic population. Fluent aphasics showed this particularly with "symbolic," content-bearing movements, while nonfluent aphasics were higher than controls in both symbolic and "motor" (simple and small) movements. No deficit in the internal organization of movement was seen in the aphasic population. These results indicate that aphasics increase their coverbal movement in compensation for their speech impairment: fluent aphasics compensate primarily for a symbolic impairment, while nonfluent aphasics compensate more for a motor impairment.

Adult↗
PubMed2004

Cancer patient survival in Sweden at the beginning of the third millennium--predictions using period analysis.

Estimates of cancer patient survival made using traditional, cohort-based, methods can be heavily influenced by the survival experience of patients diagnosed many years in the past and may not be particularly relevant to recently diagnosed patients. Period-based survival analysis has been shown to provide better predictions of survival for recently diagnosed patients and earlier detection of temporal trends in patient survival than cohort analysis. We aim to provide predictions of the long-term survival of recently diagnosed cancer patients using period analysis. The period estimates are compared with the latest available cohort-based estimates. Our results, based on period analysis for the years 2000-2002, suggest an improvement in survival for many forms of cancer during recent years. For all sites combined the 5-, 10-, 15-, and 20-year relative survival ratios were 62%, 53%, 48%, and 47% for males and 67%, 62%, 60%, and 59%, for females. These estimates were 3-14% units higher than those obtained using the latest available cohorts with the respective lengths of follow-up. The interval-specific relative survival stabilised for males at 97% after 8 years of follow-up and for females at 98% after 7 years for both period and cohort analyses.

Adolescent↗
PubMed2005

A brain-like neural network for periodicity analysis.

This paper introduces a brain-like neural model for sound processing. The periodicity analyzing network (PAN) is a bio-inspired neural network of spiking neurons. The PAN consists of complex models of neurons, which can be used for understanding the dynamics of individual neurons and neuronal networks. On a technical level, the PAN is able to compute the ratio of modulation and carrier frequency of harmonic sound signals. The PAN model may, therefore, be used in audio signal processing applications, such as sound source separation, periodicity analysis, and the cocktail party problem.

Algorithms↗
PubMed2004

Up-to-date long-term survival of cancer patients: an evaluation of period analysis on Swedish Cancer Registry data.

The natural development of cancers as well as the measures to fight the disease are often long processes that require decades of follow up. Available information on long-term survival will thus often appear outdated and irrelevant. A few years ago, period-survival analysis was proposed as a means to obtain more up-to-date information on long-term cancer survival. This article assesses period and conventional cohort-based survival analyses on their ability to predict future survival. Based on historical data from the nationwide Swedish Cancer Registry 5-, 10- and 15-year relative survival actually observed for patients diagnosed at one particular point in time are compared to the most recent period and cohort-based survival estimates available at that point in time. The study shows that period analysis can, in most cases, be used to provide more up-to-date long-term estimates of cancer survival. Period analysis reduces the time lag of the survival estimates by some 5-10 years for all cancers combined and especially affects the survival estimates for small intestine carcinoids, meningioma and intracranial neurinoma of the brain, non-seminoma testicular cancer, chronic lymphocytic leukaemia and Hodgkin's lymphoma.

Cohort Studies↗
PubMed1990

Periodicity analysis of sleep EEG in the second and minute ranges--example of application in different alpha activities in sleep.

To investigate the temporal organization of EEG sleep activity in the second and minute ranges we developed a method which, based on Fourier transformation, allows the presentation of periodic oscillations of spectral power and coherence. The application of this method is demonstrated in 3 subjects with different types of alpha activity during sleep: (a) alpha-sleep pattern (a physiological variant of NREM sleep activity); (b) abnormally increased arousal alpha activity. The results show that differences in the temporal organization of these alpha activities can be determined with the following parameters: period length, duration of sequences with periodic activity, number and rate of these sequences, and proportion of periodicities generated simultaneously in the left and right hemispheres. The physiologically modulated periodicities of the alpha-sleep pattern are contrary to a stereotyped 40-60 sec periodicity of abnormal arousal alpha activity. Such abnormal periodicity corresponds to periodicities occurring in association with other sleep disturbances, such as sleep apnea or periodic movements in sleep. Periodicity analysis gives additional criteria for a more refined evaluation of normal as well as abnormal sleep structure.

Adult↗
PubMed1977

Oscillating contractions in protoplasmic strands of Physarum: simultaneous tensiometry of longitudinal and radial rhythms, periodicity analysis and temperature dependence.

1. The construction of a 'twin-tension transducer' allows the simultaneous measurement of the same or different contraction rhythms at any selected sites of living plasmodia of Physarum polycephalum. This method has been used to analyse the relation of longitudinal and radial contraction activity within migrating plasmodia and plasmodial veins, under isometric as well as under isotonic conditions of measurement. 2. A periodicity analysis of the oscillating contraction rhythms revealed average period values for the longitudinal contraction cycle of 2-1 min and for the radial contraction cycle of 1-3 min at a temperature of 22 degrees C. 3. The periods of longitudinal contraction depend on the environment of the strands. The mean value under submerged conditions was 2-9 min. 4. The temperature dependences for both longitudinal and radial contraction cycles were determined to provide reliable values for the normal reaction range of the contractile system (cytoplasmic actomyosin). The values for radial contraction activity are 2-0 min at 16 degrees C, 1-5 min at 20 degrees C, and 1-2 min at 24 degrees C. The range between 16 degrees and 24 degrees C can be regarded as physiological. 5. The possibility is discussed that only one 'genuine' contraction frequency of cytoplasmic actomyosin exists in Physarum.

Cytoplasm↗
PubMed1984

Period analysis of the EEG in early putative Alzheimer's disease.

The EEG of patients with presumptive diagnoses of mild-to-moderate dementia of the Alzheimer type (DAT) and still residing in the community was examined using period analytic techniques. DAT patients were found to have significantly slower major and intermediate period EEG activity as compared to controls. Furthermore, one DAT patient, whose clinical EEG was read as normal, had period analytic EEG descriptors that were greater than one standard deviation below the mean of the control group. Results suggest that EEG activity, as quantified by period analysis, can be detected very early in the course of DAT.

Aged↗