Remote daily activity of Parkinson’s disease patients:             the Akinesia assessmentMatteo Pastorino*1, Laura Pastor...
the motor state and monitor response to standard and               caregivers. The sensor size is not bigger than a smalle...
interventions, such as medication and food intake and on the                            III. SUBJECTS AND PILOTSexecution ...
of the evaluation of the standard clinical protocol. This phase                                                           ...
In particular, combining the information from the activity                                                                ...
In fact, as illustrated in Figure 11 and Figure 12, theamount of energy produced during the ON stage is higher thanthe ene...
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Paper Matteo Pastorino - Remote daily activity of Parkinson’s disease patients: the Akinesia assessment

  1. 1. Remote daily activity of Parkinson’s disease patients: the Akinesia assessmentMatteo Pastorino*1, Laura Pastor-Sanz*2, Maria Teresa Arredondo*3, Jorge Cancela*4, Francisco del Pozo Guerrero5, Federico Villagra§6, Maria A. Pastor§7 * Life Supporting Technologies, ETSIT- UPM Avda. Complutense 30, Madrid, Spain 1 2 3 4 Center of Biomedical Technology, UPM # Campus Montegancedo, Pozuelo de Alarcón, Madrid, Spain. 5 § Center for Applied Medical Research, University of Navarra Avda. Pío XII 55, Pamplona, Spain 6 7 mapastor@unav.esAbstract— The aim of this paper is to describe and present the drugs for the treatment of PD, and levodopa appears mostarchitecture and assessment of Akinesia in Parkinson’s disease suitable for physiological treatment [4].(PD) patients using wireless, wearable accelerometers. The Among the symptoms ameliorated by brain dopaminecurrent work is related to a specific module of the PERFORM replacement, akinesia is of particular interest. Akinesiasystem, a FP7 project from the European Commission, thataimed at providing an innovative and reliable tool, able to includes two distinct motor disorders. One motor disorder ofevaluate, monitor and manage patients suffering from PD. akinesia is bradykinesia, which is defined as slowness ofPrevious works indicate a correlation between the lack of movement and clumsiness, is studied by evaluation ofmovement of PD patients and the OFF phase. Following this particular movements. Bradykinesia occurs in parallel withapproach, PERFORM system uses the Akinesia assessment, rigidity and impaired skilled motor performance in PDcombined with the output provided by the developed modules patients and is considered a secondary akinesia. The otherrelated to other PD symptoms (such as bradykinesia and motor disorder of akinesia is hypokinesia, defined as absencedyskinesia), in order to automatically discriminate ON and OFF of movement. This is a condition in which any automaticperiods in PD patients. movement or action, including gestures, blinking or I. INTRODUCTION swallowing actions are limited and their frequency decreases, although the elemental motor functions are maintained and Idiopathic Parkinson´s disease (PD) is a movement can be performed voluntarily. Hypokinesia may be thedisorder characterised by the triad of bradykinesia, tremor at essential feature of PD and might be labelled primary akinesiarest and muscular rigidity which results from a decreased [4]. Hypokinesia is not dominant at early stages of the disease,dopaminergic tone in the motor portions of the putamen [1]. but becomes prominent with the disease progression. It is notThese motor features, which are the principal sources of linked to the severity of rigidity, tremor, and gait dysfunction.disability, are accompanied by non-motor issues as depression, It can be considered to be simply an idle state in whichanxiety, autonomic dysfunction, sleep disorders, and cognitive patients do not move although elemental motor functions areimpairment, which are believed to result from a combination maintained [4]. Hypokinesia is not accompanied by a clearof dopamine deficiency in the non-motor portions of the decrease in motivation or impaired cognitive function [4].striatum and more widespread progressive pathologic changes Antiparkinsonian dopaminergic medications such as L-in the brainstem, thalamus and eventually the cerebral cortex DOPA and dopamine agonists ameliorate motor deficits in PD[2]. The available anatomical and physiological studies by compensating for the loss of dopamine [5]. Diseasestrongly suggest that PD results from dopaminergic progression modifies the response to Levodopa or agonistspopulation loss in the substantia nigra pars compacta which defining in the patient a pattern of clinical statues of variableinduces basal ganglia dysfunction and neuronal discharge mobility (ON state) and some wearing off periods when theabnormalities within the entire motor circuit [3]. The lack of medication ceases to be effective and patient suffer disabilitydopamine causes the motor disorder of the PD, in particular to perform precise and fast movements (OFF state). Accuratethe cardinal features of bradykinesia and akinesia symptoms. assessment of movement impairment is necessary to ascertainLevodopa and dopamine agonists are the most important
  2. 2. the motor state and monitor response to standard and caregivers. The sensor size is not bigger than a smallexperimental therapeutic interventions [6]. matchbox. Sensors on the arms and legs are attached on This paper describes a solution for the objective detection specially designed elastic Velcro bands, which allow fixationand assessment of Akinesia in order to better adjust to any wrist or ankle size. The sensors are placed inside anmedication schedules and personalise treatment of Parkinson’s elastic pocket on the band, which secures it firmly on thedisease (PD) patients. The work has been carried out within patient body avoiding motion artefact due to cloth movement.the framework of PERFORM [8] FP7 European project, The sensor on the trunk is placed within a zipped elasticpartially funded by the EU, which included the development pocket on a vest. The vest is also equipped with Velcro strapsof an intelligent system that integrates a wide range of to firmly adjust the sensor on the patient chest. The selectedwearable sensors (Figure 1) that constantly record the motor design allows the easy wearing and attachment/detachment ofsignals of the PD patients. Data acquired are pre-processed by sensors.advanced knowledge processing methods, and integrated byfusion algorithms to allow health professionals to remotelymonitor the overall status of the patients, adjust medicationschedules and dosages, and personalise the treatment [9]. II. SYSTEM FOR DATA COLLECTION The PERFORM project is based on the development of anintelligent loop system (Figure 5) that seamlessly integrates awide range of wearable micro-sensors constantly monitoringseveral motor signals of the patients. Personalisation oftreatment occurs through PERFORM‘s capability to keeptrack of the timing and doses of the medication and meals thatthe patient is taking.A. Monitoring System The wearable device used to recording the motor signals Figure 2 - PERFORM system placementconsists of a tri-axial accelerometers’ set used to record the Once the data has been stored in the SD card, the patientaccelerations of the movements at each patient limb, one needs to connect the logger to a PC where the patient unit,accelerometer and gyroscope (on the belt) used to record body called Local Base Unit (LBU) is responsible for themovement accelerations and angular rate, and a data logger identification and quantification of the patient symptoms and(also located on the belt) that receives and stores all recorded the recording of other useful information for the evaluation ofsignals in a SD card (Figure 2). Sensors allow the system the patient status.detecting and quantifying a wide range of symptoms andmeasures of Parkinson’s disease patient i.e. tremor, B. Patient Interfacebradykinesia, dyskinesias and freezing of gait. All sensors Emphasis is given to the design of an interface easy to usetransmit data using Zigbee protocol to a logger device, with for the patient, considering the patient motor disabilities and62.5 Hz sampling rate (16 milliseconds between samples). limited computer familiarity. The designed interface inherits the look and feel of the phone dialling pad, and all system choices are based on it. Figure 3 - Patient Interface Meals Questionnaire Figure 1 – PERFORM Monitoring System Prototype The patients use the interface to declare their subjective Special attention was paid in order to ensure the monitoring estimation of their own status, to gain access to relevantsystem usability and an easy placement for the patient and the disease information, to receive instructions on life-style
  3. 3. interventions, such as medication and food intake and on the III. SUBJECTS AND PILOTSexecution of tests. Moreover, PD’s patients declare This section describes the evolution of the PERFORMmedication intake information, which is useful for the patient project, the devices used and the procedures followed tostatus assessment. collect and process the signals, highlighting the problems found and the solutions provided during the different phases. A. Phase I: Data Collection with SHIMMERS Eight subjects participated in this study, classified into two different groups: four PD patients and four healthy subjects. The symptoms were rated by a professional neurologist with more than 20 years of experience with PD patients. Four accelerometers were placed on the right and left forearms and on the right and left calves, with a fifth accelerometer being placed on the trunk, at the base of the sternum. Motion data was collected using the SHIMMER platform. SHIMMER is a small cordless sensor platform designed by Intel® as a wearable device for healthsensing applications. All sensors Figure 4 - Patient Interface Medication Questionnaire provide 3-axis accelerometric signals and large storage andC. Local Base Unit low-power standards based communication capabilities. They This submodule processes the patient signals acquired and also provide a Bluetooth protocol capability that allowsdetects the targeted patient symptoms (tremor, levodopa SHIMMERs to stream the data to a computer.induced dyskinesia and off state). For each symptom, adedicated submodule processes the relevant signals, detectsthe symptom episode and quantifies it into a severity scalefrom 1 to 4, according to the UPDRS (Unified Parkinson’sDisease Rating Scale) scaling for PD patients [7]. Otherfeatures such as duration, frequency and amplitude might alsobe provided for further clinician review and system evaluation.D. Central Hospital Unit This module exploits the recorded patient information in Figure 6 - SHIMMER Sensororder to build a patient symptom profile. For each main During the experiment, the accelerometer measurementssymptom (tremor, levodopa induced dyskinesia and on-off were complemented by a reflective marker and a videostates), it produces a patient profile which describes the camera recording system. This complimentary analysis servedpatient’s common symptom features. When a new patient as a support tool to validate the data used for this work.recording is processed, it is compared with the patientsymptom profile. If significant differences are found, it might B. Phase II: Data Collection with ANCO first release trainerbe due to two reasons: either a temporarily patient behaviour classifierabnormality or a change in the patient profile. In the last case, The data collection in this phase was performed with athe system checks whether a substantial number of similar network of wireless 3-axis ALA-6g (ANCO, Athens, Greecesituations are identified for the last time period for the specific [11]) sensors, located on the limbs, trunk and belt of thepatient and if that occurs, it creates an alert. patient. During this phase, data were collected on test patients in a supervised environment, with the collaboration of the clinic’s medical staff. Patients involved in this phase were required to be aged between 18 and 85 years old, suffering from PD, capable of complying with study requirements, receiving stable dopaminergic treatment and experiencing motor fluctuations. Dementia, psychosis and significant systemic diseases (such as cancer) were the exclusion criteria applied when selecting participants. The data set used in this study included trials with twenty PD patients, ten in Navarra (Spain) and ten in Ioannina (Greece). In order to comply with ethical requirements, all procedures were carried with the Clinic Institutional Review Board’s permission. Figure 5 - PERFORM Loop System
  4. 4. of the evaluation of the standard clinical protocol. This phase included trials with twelve patients in Pamplona (Spain) and twelve patients in Ioannina (Greece). D. Phase IV: System Evaluation A group of 25 patients, after assessing the usability of the PERFORM project, accepted to participate in the study. Figure 7 - PERFORM Sensors First Release Each subject performed a supervised protocol both duringgood clinical condition (ON status), and during the wearingoff efficiency of the medication (OFF status). The followingprotocol tasks were recorded with a video camera and thesensors twice a day meanwhile the patient was hospitalised.The patient was requested to lie down in a hospital bed for 5minutes; to sit down on a chair for 5 minutes in order to Figure 8 - Technical Tests in Modena -Italyrecord a possible resting tremor. Then he/she was asked tostand up from the chair and perform a series of activities: walk During the phase IV, data were collected in anfor a distance of 5 m, open a door to get into the room (could unsupervised environment and with the collaboration of abe the bathroom), close the door and then open the door, step caregiver during a week. Data were acquired during an eight-out of the room and close the door again. Then he/she hour daily session in which patients carried out their normalcontinued by leaving the hospital room and walking through daily activity. Furthermore, patients involved in this phase,the corridor for a straight distance of 10 meters. At the end of fulfilled with the age and medical specifications of thesuch distance he/she was requested to turn and walk back to previous phase.the room. Midway he was asked to stop and drink from a glass A standard UPDRS [7] clinical evaluation was performedof water located on a table. Subsequently the patient was during the first and the last day, in order to compare the outputasked to return to his/her room and sit down on the chair of the system with clinical assessment provided by the doctor.where another 5 minutes of recordings were completed. Moreover, patients filled in a diary in order to compare their subjective evaluation about their overall daily status with theC. Phase 3: Long time recording results of the PERFORM system. Data collection of phase III was performed with an The protocol was approved by Ethical Committee ofimproved version of the devices that includes a wearable and University of Modena in July 2010, and the PERFORM’sprogrammable logger that gives a better mobility to the hardware system was approved by the Technical Departmentpatients and new ALA-6 g accelerometers sensors equipped of the “Nuovo Ospedale Civile S.Agostino-Estense”.with an external battery that allows longer data collectionsessions. IV. METHODOLOGY During the phase III, data were collected during a week in A. System description and classification methodan unsupervised environment and with the collaboration of acaregiver. Data were acquired during an eight-hour daily During the first phase of the PERFORM project, ansession in which patients carried out their normal daily intelligent system, that monitors the motor signals of theactivity. Furthermore, patients involved in this phase, patients, was developed in order to detect the symptomscomplied with the age and medical specifications of the episodes and quantify them into a severity scale ranging fromprevious phase. Moreover, two daily standard clinical protocol 0 to 4, according to the UPDRS [7] scale for PD patients. Insessions were performed during the trials under the particular, this paper presents the results of an algorithmsupervision of a clinician. The neurologist examined the developed in order to measure the Akinesia. Once data arepatients performing the UPDRS [7] protocol twice a day, both stored in the patient device (usually a PC), the LBUduring the ON and OFF stages. Subsequently, the protocol automatically starts the signal process [10].sessions were video recorded and matched with the data Different modules were created in order to detect andlogger and sensors recordings. During the protocol session the quantify different symptoms as shown in Figure 9.patients carried out twice a day the following activities: sit, This module assesses the amount of movement of theread, drink a glass of water and walk for approximately two patient in space for any given period of time. The amount ofminutes. At the end of the day, data were processed using the movement is a metric that is associated with the PD symptomtraining set computed in Phase II and the output was akinesia. “Amount of movement” and “Akinesia” are relatedcompared with the results provided by the clinician, as a result terms. [opposed terms]
  5. 5. In particular, combining the information from the activity recogniser module, which detects whether the patient is walking or moving his hands, together with the output of the akinesia one, it is possible to discriminate the ON and the OFF phase, based on the general level of energy produced by a PD patient during a short period of time (5 minutes). In Figure 10 an example of the akinesia computed during a period of time of 4 hours is shown. The blue area defines the walking period, while the grey one defines the no-walking period. The green line indicates the amount of energy Figure 9 - Signal process schema of LBU produced during a short period of time, while the black line defines the ON (lower level) and OFF state (upper level), This symptom has clinical significance upon itself; in fact, according to the patient is mentioned in the UPDRS [7] in question 29. The answers In order to analyse the results of the output of the akinesiato the question though, are related to Bradykinesia, so the module, the mean value is computed during both the ON andresults of Akinesia are directly presented to the doctor, OFF periods.without any upper level processing being devoted to Akinesiaitself, not in a direct way. However, it is worth clarifying that the output of thismodule will contribute to upper-level processing in an indirectway. Previous studies in Radboud University, the Netherlands,also mentioned the positive impact that taking Akinesia intoaccount has in automatically discriminating ON from OFFperiods in PD patients. The model works by calculating theenergy combining the signals acquired by the sensors worn bythe patients. The measure gives an assessment of the quantityof movement during a specific time interval. To calculate this,the signal is split into 5 minute windows, filtered (LPF at 3  Hz) and the energy of the signal is obtained for each window Figure 11 - ON/OFF difference for NO WALKING periodof time, with 50% of overlapping. The resulting energies of For the analysis of the results, two different scenarios areeach sensor are combined by using a weighted sum in order to considered. The first scenario (Figure 11) compares the meantake into account all the possible combination of sensors. value of the computed akinesia during the periods when theB. On/Off evaluation using the Akinesia patient is not walking. The green bar identifies the mean value of the akinesia during the ON period, while the red one Analysing graphics referring to Akinesia, detected by the represents the mean value of the akinesia during the OFFPERFORM system by the parameter energy, it is possible to period.observe a clear relationship between the detected ON-OFF Following the same approach, the second scenario (Figurephases and the akinesia levels. There is a strong correlation 12) compares the mean value of the computed akinesia duringbetween the lack of movement of PD patients and the OFF walking periods.status. Using the akinesia assessment, combined with theoutput provided by the developed modules related to othersymptoms (such as bradykinesia and dyskinesia), it is possibleto discriminate ON and OFF periods in PD patients. Figure 12 - ON/OFF difference for WALKING period The global evaluation of both scenarios demonstrates that it is possible to discriminate ON and OFF periods computing the lack of movement combining the information provided by different modules of the PERFORM system, in this case the activity recognizer and the Akinesia module. Figure 10 – Akinesia computed during a 4 hours recording session
  6. 6. In fact, as illustrated in Figure 11 and Figure 12, theamount of energy produced during the ON stage is higher thanthe energy produced during the OFF stage. V. CONCLUSIONS The results obtained so far are very promising, since theyindicate that PERFORM is an objective tool, suitable forclinical practice that will support health professionals in thediagnosis and follow-up of PD patients and therefore willcontribute to the patients’ quality of life improvement. The results presented are computed using the recording ofone patient during 4h and are focused only in the akinesiaresults as discriminating parameter for the ON – OFFcondition assessment in PD. Future works will include a more exhaustive analysis usingall the recordings collected during the pilot phases combiningthe results of all PERFORM classifier outputs in order tocreate a complete profile of patients. ACKNOWLEDGMENTS Authors thank the PERFORM consortium for theircontribution to this work, especially the University Clinic ofNavarra, the University of Ioannina and the Nuovo OspedaleCivile S.Agostino-Estense of Modena. REFERENCES[1] M.R. Delong and T. Wichmann, Circuits and circuits disorders of the basal ganglia. Arch. Neurol., 2007; 64 (1): 20-24.[2] H. Braak, K. Del Tredici, U. Rub, R.A. de Vos, E.N. Jansen Steur and E. Braak, Staging of brain pathology related to sporadic Parkinsons disease. Neurobiol Aging. 2003; 24:197-211.[3] T. Wichmann, M.R Delon, J. Guridi and J.A Obeso, Milestones in Research on the Pathophysiology of Parkinson´s Disease. Movement Disorders, vol 26 (6): 1032-1041, May 2011[4] M. Yokochi, Reevaluation of levodopa therapy for the treatment of advanced Parkinson´s disease. Parkinsonism and Related Disorders 15, Supplement 1 (2009); S25-S30.[5] Y. Kwak, L.T.M. Martijn Muller, N.I. Bohnen, P. Dayalu and R.D. Seidler, Effect of Dopaminergic Medications on the Time Course of Explicit Motor Sequence Learning in Parkinson’s Disease. J Neurophysiol 103: 942–949, 2010. J Neurophysiol 103: 942–949, 2010.[6] A. J. Espay, J.P. Giuffrida, R. Chen, M. Payne, F. Mazzella, E. Dunn, J.E. Vaughan, A.P. Duker, A. Sahay, S.J. Kim, F.J. Revilla, and D.A. Heldman, Differential Response of Speed, Amplitude, and Rhythm to Dopaminergic Medications in Parkinson’s Disease.[7] Movement Disorder Society Task Force on Rating Scales for Parkinson’s disease. The Unified Parkinson’s Disease Rating Scale (UPDRS): Status and Recommendations. Movement Disorders Vol. 18, No. 7, 738-750 (2003)[8] PERFORM project (IST- 215952) Annex I- Description of Work 2007[9] J. Cancela, M. Pansera, M.T. Arredondo, J.J. Estrada, M. Pastorino and L. Pastor-Sanz, “A comprehensive motor symptom monitoring and management system: the bradykinesia case”. Conference proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1008-11. 2010, August 31 – September 4[10] M. Pastorino, J. Cancela, M.T. Arredondo, M. Pansera, L. Pastor-Sanz, F. Villagra, M.A. Pastor and J.A Martín, “Continuous monitoring and assessment of Bradykinesia in Parkinson’s disease patients through a multi-parametric system”. Conference proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1810-13. 2011, August 30 – September 3[11] ANCO SA website. [Online]. Available: