Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Dialekter och röstigenkänning : Ett röstigenkännings-API:s förmåga att uppfatta svenska dialekters kännetecken och röstkombinationer

Allt eftersom utvecklingen går framåt inom applikationer och system så förändras också sättet på vilket vi interagerar med systemet på. Hittills har navigering och användning av applikationer och system mestadels skett med händerna och då genom mus och tangentbord. På senare tid så har navigering via touch-skärmar och rösten blivit allt mer vanligt. Då man ska styra en applikation med hjälp av rösten är det viktigt att vem som helst kan styra applikationen, oavsett vilken dialekt man har. För att kunna se hur korrekt ett röstigenkännings-API (Application Programming Interface) uppfattar svenska dialekter så initierades denna studie med dokumentstudier om dialekters kännetecken och ljudkombinationer. Dessa kännetecken och ljudkombinationer låg till grund för de ord vi valt ut till att testa API:et med. Varje dialekt fick alltså ett ord uppbyggt för att vara extra svårt för API:et att uppfatta när det uttalades av just den aktuella dialekten. Därefter utvecklades en prototyp, närmare bestämt en android-applikation som fungerade som ett verktyg i datainsamlingen. Då arbetet innehåller en prototyp och en undersökning så valdes Design and Creation Research som forskningsstrategi med datainsamlingsmetoderna dokumentstudier och observationer för att få önskat resultat. Data samlades in via observationer med prototypen som hjälpmedel och med hjälp av dokumentstudier. Det empiriska data som registrerats via observationerna och med hjälp av applikationen påvisade att vissa dialekter var lättare för API:et att uppfatta korrekt. I vissa fall var resultaten väntade då vissa ord uppbyggda av ljudkombinationer i enlighet med teorin skulle uttalas väldigt speciellt av en viss dialekt. Ibland blev det väldigt låga resultat på just dessa ord men i andra fall förvånansvärt höga. Slutsatsen vi drog av detta var att de ord vi valt ut med en baktanke om att de skulle få låga resultat för den speciella dialekten endast visade sig stämma vid två tillfällen. Det var istället det ord innehållande sje- och tje-ljud som enligt teorin var gemensamma kännetecken för alla dialekter som fick lägst resultat överlag.

Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease

OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device. BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299). METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores. RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55). CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.

Gamers preferenser för användargränssnitt på en spelrelaterad webbplats

Användargränssnittsdesign är en stor del av en webbsidas intryck och förändras snabbt i takt med teknologins utveckling och trender. Men det gäller även att locka rätt användare. Hur lockar en webbsida till sig rätt målgrupp? Målet med rapporten var att analysera målgruppen gamers utifrån hur de upplever det grafiska användargränssnittet på en spelrelaterad webbsida. Rapporten behandlar även översiktitligt om aktuella trender för webbdesign tilltalar gamers. Undersökningen utfördes i två delar. I den första delen undersöktes 20 av de största spelrelaterade webbsidornas användargränssnitt. Under del två genomfördes en enkät och intervjuer med målgruppen gamers. I både enkäten och intervjuerna fick respondenterna ta ställning till olika mockups av en fiktiv webbsida. Det var stor skillnad på vad gamers ansåg vara tilltalande jämfört med hur de analyserade webbsidorna såg ut. Exempelvis var endast 25 % av de analyserade webbsidorna mörka medan 71,9 % av respondenterna föredrog en mörk layout.

Effekter av massage/beröring hos dementa respektive icke dementa äldre personer : Systematisk litteraturstudie med empiriskt tillägg

Föreliggande systematiska litteraturstudie syftade till att kartlägga vad som fanns beskrivet i litteraturen om effekter av massage/beröring hos dementa respektive icke dementa äldre personer. Syftet var även att kartlägga personalens inställning till massage/beröring och denna omvårdnads- åtgärds effekter empiriskt. Artiklarna har sökts i Högskolan Dalarnas fulltextdatabas ELIN för vidare granskning. Artiklarna som valdes var från åren 1999-2009. Sökorden som användes var massage, older, elder, old*, geriatric, demen*, touch, effects, tactil. Av resultatet framkom att i större delen av studierna har massage/beröring en positiv effekt på välmående hos äldre dementa och icke dementa människor. Särskilt kunde noteras att massage kunde vara en metod att minska agiterat beteende och vandrande hos dementa personer. Personalens inställning till massage/beröring sågs som positiv i den bemärkelsen att massage/beröring gynnade patientens välmående och att personalen kunde interagera med patienten på ett mer positivt sätt. I det empiriska tillägget var huvudfyndet att massage/ beröring hade bättre effekt för sömnen för dementa än för icke dementa. Uttryckt i Martinsens omvårdnadsteoretiska termer måste omvårdnaden ha som utgångspunkt den andres bästa. För att komma fram till vad som är bäst för den andre måste man vara öppen och närvarande hos honom samt sträva efter att tolka hans situation och behov. Föreliggande studies resultat bidrar till kunskap om massage/beröring som metod för äldre med särskild betoning på demens.

Beröringens betydelse i vårdandet av cancerpatienter – en litteraturöversikt

Bakgrund: Beröringen är ett av människans grundläggande behov. Närhet och beröring har betydelse för välbefinnandet. Beröring är en central del i vårdandet, där den är förväntad och accepterad. Att leva med cancer innebär ett stort lidande. Både fysiskt, psykiskt, socialt och existentiellt. Många genomgår tuffa behandlingar med biverkningar, vilket skapar ett lidande för både patient och närstående. Syfte: Syftet med denna litteraturöversikt var att beskriva beröringens betydelse i vårdandet av cancerpatienter. Metod: En litteraturöversikt, där femton vårdvetenskapliga artiklar har använts, nio med kvantitativ metod och sex med kvalitativ metod. Resultat: Studiens resultat visade att beröring har betydelse i omvårdnaden av cancerpatienter, både i livets slut och hos de som genomgår tuffa behandlingar. Beröring dämpade svåra biverkningar såsom illamående, oro/ångest, smärta samt att lindra lidandet. Patienterna upplevde ökad livskvalitet. Beröringen hade även en positiv betydelse för patienternas relation med både sjuksköterskan och anhöriga. Slutsats: Att drabbas av cancer innebär ett stort lidande, både fysiskt, psykiskt, socialt och existentiellt. Litteraturöversikten visar att beröring som omvårdnadsåtgärd hjälper patienterna att öka sitt välbefinnande på alla dessa fyra plan. Genom att använda beröring inom vårdandet av cancerpatienter kan man öka deras livskvalité och välbefinnande.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.

Beröringsbehandling hos patienter med cancer : En litteraturöversikt

Bakgrund: Varje år diagnostiseras cirka 64 000 personer med cancer och tumörsjukdomar är den näst vanligaste dödsorsaken i Sverige. Att få diagnosen cancer innebär en påfrestande tid både fysiskt och psykiskt. Sjuksköterskans arbetsuppgift är bland annat att lindra lidande och främja för god hälsa. Beröring är ett allmänmänskligt livslångt behov och blir extra tydligt när en dödlig sjukdom drabbar en människa. Syfte: Syftet är att belysa erfarenheter av beröringsbehandling hos sjuksköterskor och patienter med cancer. Metod: Studien har valt att genomföras som en litteraturöversikt, där 14 vetenskapliga artiklar användes varav 5 kvalitativa och 9 kvantitativa. Resultat: Resultatet delades in i två områden: Patienters erfarenheter av beröringsbehandling och sjuksköterskors erfarenheter av beröringsbehandling. Under området patienters erfarenheter framkom två kategorier: lindrande inverkan och främjande inverkan, samt underkategorierna: fysiskt obehag, psykiskt obehag, välbefinnande och närhet. Under området sjuksköterskors erfarenheter framkom en kategori: utbildning i beröringsbehandling samt underkategorin: upplevelser av beröringsbehandling. Slutsats: Beröringsbehandling har en kortvarig symtomlindrande inverkan på smärta, ångest, illamående samt ger ökat välbefinnande och livskvalitet. Därtill förbättrades kontakten mellan sjuksköterska och patient som bidrog till att den existentiella ensamheten minskades. Sjuksköterskorna såg patienten som en individ istället för en patient med en sjukdom.

Effekter av icke-farmakologiska metoder vid beteendemässiga och psykiska symtom hos personer som lever med Alzheimers sjukdom : En litteraturöversikt

Bakgrund: Alzheimers sjukdom (AD) är den vanligaste formen av demenssjukdomar och antalet människor som insjuknar i AD förväntas öka kraftigt med tiden. Dessutom kännetecknas personer med AD ofta av beteendemässiga och psykiska symtom (BPSD) som kan innefatta agitation, depression, vanföreställningar, oro, ångest, hallucinationer, sömnrubbningar, rastlöshet och apati. Dessa symtom kan orsaka lidande hos patienten och är svåra att hantera för både vårdgivaren och anhöriga, samt försvårar omvårdnadsarbetet. Syftet var att beskriva icke-farmakologiska metoder och effekter av dessa metoder vid omvårdnad av personer med Alzheimers sjukdom som har beteendemässiga och psykiska symtom. Metod: En litteraturöversikt bestående av 16 utvalda kvantitativa forskningsartiklar har genomförts. Artiklarna publicerades mellan år 2006-2016. Resultat. De studerade icke-farmakologiska metoderna var musikterapi, vissa typer av massage, reminiscence-terapi, vårdhundterapi och ljusterapi. Resultaten visade att icke-farmakologiska metoder kan ha en varierande effekt på BPSD. Litteraturöversikten visade att musikintervention var mest effektiv för att minska agitationsbeteende. Individualiserad musik i samband med speciella minnen minskade stress, fobier hos personer med svår demens. Intervention av handmassage, aromaterapi, taktil massage och terapeutisk beröring minskade aggression och agitationsbeteende. Vissa studier visade dock att fotmassageintervention och vårdhundterapi kunde öka verbal aggressivitet hos personer med demens, medan en annan studie visade att djurassisterade aktiviteter kunde minska nedstämdhet medan glädje och generell uppmärksamhet ökade. Effekten av ljusbehandling var förbättrad sömn, minskad depression, agitation och ätstörningar. Slutsats. Icke-farmakologiska metoder kan minska beteendemässiga och psykiska symtom hos personer med Alzheimers sjukdom, dock med varierande effekt. De varierande resultaten kan tolkas som att icke-farmakologiska metoder bör individanpassas och att det behövs vidare forskning inom området.

A review of Parkinson’s disease cardinal and dyskinetic motor symptoms assessment methods using sensor systems

This paper is reviewing objective assessments of Parkinson’s disease(PD) motor symptoms, cardinal, and dyskinesia, using sensor systems. It surveys the manifestation of PD symptoms, sensors that were used for their detection, types of signals (measures) as well as their signal processing (data analysis) methods. A summary of this review’s finding is represented in a table including devices (sensors), measures and methods that were used in each reviewed motor symptom assessment study. In the gathered studies among sensors, accelerometers and touch screen devices are the most widely used to detect PD symptoms and among symptoms, bradykinesia and tremor were found to be mostly evaluated. In general, machine learning methods are potentially promising for this. PD is a complex disease that requires continuous monitoring and multidimensional symptom analysis. Combining existing technologies to develop new sensor platforms may assist in assessing the overall symptom profile more accurately to develop useful tools towards supporting better treatment process.