On the filtering of photoplethysmography signals

© 2014 IEEE. Recently there has been renewed interest in the application of photoplethysmography signals for cardiovascular disease assessment. Photoplethysmography signals are acquired non-invasively using visible and infrared light passed through the finger pulp. Unfortunately, this method commonly suffers from many forms of interference and distortion such as; baseline wander, mains-line interference and random spikes or other such artifacts. This paper presents a new approach for effective filtering of the photoplethysmography signal. Specifically, a cascaded filtering method for removing the artifacts from photoplethysmography signals based on the median and polynomial filters (MdPF) is proposed. Recordings from the PhysioNet database are used to validate the proposed method. Our experimental results show that the performance of MdPF cascaded filtering method is more effective than other current methods alone in removing artifacts from photoplethysmography signals. Root mean square error measurements are used for comparison purposes. This paper follows from previous work on median based method for baseline wander removal in photoplethysmogram signals

Median based method for baseline wander removal in photoplethysmogram signals

© 2014 IEEE. Removal of baseline wander is a crucial step in the signal conditioning stage of photoplethysmography signals. Hence, a method for removing the baseline wander from photoplethysmography based on two-stages of median filtering is proposed in this paper. Recordings from Physionet database are used to validate the proposed method. In this paper, the twostage moving average filtering is also applied to remove baseline wander in photoplethysmography signals for comparison with our novel two-stage median filtering method. Our experiment results show that the performance of two-stage median filtering method is more effective in removing baseline wander from photoplethysmography signals. This median filtering method effectively improves the cross correlation with minimal distortion of the signal of interest. Although the method is proposed for baseline wander in photoplethysmography signals, it can be applied to other biomedical signals as well

Automated Semmes Weinstein monofilament examination replication using optical imaging and mechanical probe assembly

The World Health Organization reports more than 135 million people globally suffer from diabetes, with 25% developing peripheral neuropathy and estimates the numbers living with diabetes will reach over 300 million by 2025. Peripheral neuropathy is a term used to describe the loss of feeling in the peripheral limbs. If not properly managed, amputation of the lower limbs can be the result. Regular screening is required for this condition so as to avoid further deterioration. This paper describes an automated peripheral neuropathy testing device replicating the widely accepted Semmes Weinstein Monofilament Examination. In this paper a patient’s foot is scanned optically and the subsequent image processing and grid information algorithms presented reliably identify the plantar surface sensory neuropathy pressure points on a given patient’s foot. Then, these coordinates are relayed to an automated mechanical probe driven by a microcontroller where it randomly applies the accepted 98mN (10g) of force to those pressure points

Automated Peripheral Neuropathy Assessment using Optical Imaging and Foot Anthropometry

A large proportion of individuals who live with type-2 diabetes suffer from plantar sensory neuropathy. Regular testing and assessment for the condition is required to avoid ulceration or other damage to patient’s feet. Currently accepted practice involves a trained clinician testing a patient’s feet manually with a hand-held nylon monofilament probe. The procedure is time-consuming, labor-intensive, requires special training, is prone to error and repeatability is difficult. With the vast increase in type-2 diabetes, the number of plantar sensory neuropathy sufferers has already grown to such an extent as to make a traditional manual test problematic. This paper presents the first investigation of a novel approach to automatically identify the pressure points on a given patient’s foot for the examination of sensory neuropathy via optical image processing incorporating plantar anthropometry. The method automatically selects suitable test points on the plantar surface that correspond to those repeatedly chosen by a trained podiatrist. The proposed system automatically identifies the specific pressure points at different locations, namely the toe (hallux), metatarsal heads and heel (Calcaneum) areas. The approach is generic and has shown 100% reliability on the available database used. The database consists of Chinese, Asian, African and Caucasian foot images

New natural gradient algorithm for cyclostationary sources

A new natural gradient type algorithm (NGA) for the separation of cyclostationary sources is introduced. Based on the interpretation of blind source separation (BSS) as a two-stage process, including prewhitening and rotation, the cyclostationary NGA (CSNGA) algorithm is constructed such that it also ensures that the recovered sources are decorrelated in the cyclostationary sense. The method is generalised to the case of complex valued source signals, and modified so that adequate algorithm performance is attained even when only one source cycle frequency is known. The properties of the new algorithm are investigated when additive white Gaussian noise is present, and it is found that, in general, the CSNGA approach improves the convergence properties of the natural gradient algorithm. Computer simulations support the validity of the approach

New natural gradient algorithm for cyclostationary sources

A new natural gradient type algorithm (NGA) for the separation of cyclostationary sources is introduced. Based on the interpretation of blind source separation (BSS) as a two-stage process, including prewhitening and rotation, the cyclostationary NGA (CSNGA) algorithm is constructed such that it also ensures that the recovered sources are decorrelated in the cyclostationary sense. The method is generalised to the case of complex valued source signals, and modified so that adequate algorithm performance is attained even when only one source cycle frequency is known. The properties of the new algorithm are investigated when additive white Gaussian noise is present, and it is found that, in general, the CSNGA approach improves the convergence properties of the natural gradient algorithm. Computer simulations support the validity of the approach

Perspectives on the diagnosis and management of functional cognitive disorder: An international Delphi study.

BACKGROUND: Current proposed criteria for functional cognitive disorder (FCD) have not been externally validated. We sought to analyse the current perspectives of cognitive specialists in the diagnosis and management of FCD in comparison with neurodegenerative conditions. METHODS: International experts in cognitive disorders were invited to assess seven illustrative clinical vignettes containing history and bedside characteristics alone. Participants assigned a probable diagnosis and selected the appropriate investigation and treatment. Qualitative, quantitative and inter-rater agreement analyses were undertaken. RESULTS: Eighteen diagnostic terminologies were assigned by 45 cognitive experts from 12 countries with a median of 13 years of experience, across the seven scenarios. Accurate discrimination between FCD and neurodegeneration was observed, independently of background and years of experience: 100% of the neurodegenerative vignettes were correctly classified and 75%-88% of the FCD diagnoses were attributed to non-neurodegenerative causes. There was <50% agreement in the terminology used for FCD, in comparison with 87%-92% agreement for neurodegenerative syndromes. Blood tests and neuropsychological evaluation were the leading diagnostic modalities for FCD. Diagnostic communication, psychotherapy and psychiatry referral were the main suggested management strategies in FCD. CONCLUSIONS: Our study demonstrates the feasibility of distinguishing between FCD and neurodegeneration based on relevant patient characteristics and history details. These characteristics need further validation and operationalisation. Heterogeneous labelling and framing pose clinical and research challenges reflecting a lack of agreement in the field. Careful consideration of FCD diagnosis is advised, particularly in the presence of comorbidities. This study informs future research on diagnostic tools and evidence-based interventions