Shoulder and elbow muscle activity during fully supported trajectory tracking in people who have had a stroke A.M. Hughes a, * , C.T. Freeman b , J.H. Burridge a , P.H. Chappell b , P.L. Lewin b , E. Rogers b a School of Health Sciences, University of Southampton, Southampton, SO17 1BJ, UK b School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK article info Article history: Received 19 February 2009 Received in revised form 4 August 2009 Accepted 6 August 2009 Keywords: Stroke Electromyography Muscle activation patterns Reach Arm movement Robot abstract An inability to perform tasks involving reaching is a common problem for stroke patients. This paper pro- vides an insight into mechanisms associated with recovery of upper limb function by examining how stroke participants’ upper limb muscle activation patterns differ from those of neurologically intact par- ticipants, and how they change in response to an intervention. In this study, five chronic stroke participants undertook nine tracking tasks in which trajectory (orien- tation and length), speed and resistance to movement were varied. During these tasks, EMG signals were recorded from triceps, biceps, anterior deltoid, upper, middle and lower trapezius and pectoralis major. Data collection was performed in sessions both before, and after, an intervention in which participants performed a similar range of tracking tasks with the addition of responsive electrical stimulation applied to their triceps muscle. The intervention consisted of eighteen one hour treatment sessions, with two par- ticipants attending an additional seven sessions. During all sessions, each participant’s arm was sup- ported by a hinged arm-holder which constrained their hand to move in a two dimensional plane. Analysis of the pre intervention EMG data showed that timing and amplitude of peak EMG activity for all stroke participants differed from neurologically intact participants. Analysis of post intervention EMG data revealed that statistically significant changes in these quantities had occurred towards those of neu- rologically intact participants. Ó 2009 Elsevier Ltd. All rights reserved. 1. Introduction Following stroke, many people have a complex pattern of upper limb motor impairments resulting in a loss of functional abilities, such as reaching. The relationship between reaching and indepen- dence is reflected in measures of functional independence, such as the Barthel ADL index (van der Putten, 1999), where the ability to reach is required for over 50% of the activity of daily living tasks. The prognosis for upper limb recovery following stroke is poor; a systematic review (Hendricks, 2002) concluded that complete mo- tor recovery of the upper extremities occurs in less than 15% of pa- tients with initial paralysis. (Broeks et al., 1999) found that half of all stroke patients receiving conventional rehabilitation failed to regain upper limb function. As stroke is an age related disease, changes in demographics will increase the burden on long term health and social resources unless improvements are made in achieving independence (National Audit Office, 2005). Research into novel therapies, such as Functional Electrical Stimulation (FES) and rehabilitation robotics, strongly emphasises the importance of intensity of practice of a task (Winstein, 2004; Inaba et al., 1973), as well as variety and feedback (Magill, 1998). Use of the former approach is supported clinically (De Kroon, 2002), and theoretically from neurophysiology (Burridge and Ladouceur, 2001; Rushton, 2003) and motor learning research (Schmidt and Lee, 1999). Furthermore, the potential of FES is en- hanced when it is associated with the person’s intention to move (De Kroon et al., 2005), thereby promoting the need for precisely controlled stimulation. However, although systems have been developed in which electrical stimulation is triggered by muscle activity (Francisco et al., 1998), techniques in clinical use have not yet used feedback to adjust stimulation parameters during the task. This therefore limits their ability to produce accurate tracking. Moreover, no systems have been developed that precisely adapt the input in response to the users’ performance, in order to provide only the minimum level of stimulation needed to assist the participant’s completion of the task. Systematic reviews of the robotic therapy literature for the upper limb suggest that robot aided therapy improves motor con- trol of the proximal upper limb and may improve functional out- comes (Prange, 2006; Kwakkel et al., 2008). Repetitive task orientated movements are often practiced with the arm fully 1050-6411/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.jelekin.2009.08.001 * Corresponding author. Tel.: +44 (0)23 8059 5191. E-mail address: ah10@soton.ac.uk (A.M. Hughes). Journal of Electromyography and Kinesiology 20 (2010) 465–476 Contents lists available at ScienceDirect Journal of Electromyography and Kinesiology journal homepage: www.elsevier.com/locate/jelekin